Total 39 network engineer job vacancies in Information Technology category in Singapore

Job Summary: We are seeking an experienced and detail-oriented Network Security Engineer to join our team. The ideal candidate will have hands-on experience in managing and configuring Cisco wireless infrastructure, switches, and routers, as well as proficiency with Palo Alto and Checkpoint Firewalls.

Key Responsibilities:

• Cisco Wireless Infrastructure Management:

o Configure, deploy, and manage Cisco wireless access points and controllers to ensure reliable wireless network connectivity.

o Troubleshoot and resolve issues related to wireless network performance, coverage, and security.

o Managing the Cisco ISE.

• Cisco Switches and Routers Management:

o Install, configure, and maintain Cisco switches and routers for optimal network performance.

o Perform network troubleshooting, identify bottlenecks, and implement solutions to ensure network reliability.

• Firmware Upgrades:

o Upgrade firmware for wireless devices, routers, and switches as part of regular network maintenance and improvement.

o Ensure minimal disruption during firmware updates and troubleshooting any issues that arise.

• Network Monitoring with SolarWinds:

o Utilize SolarWinds for continuous monitoring of the network infrastructure, including switches, routers, and wireless systems.

o Respond to alerts, troubleshoot network issues, and optimize network performance based on monitoring data.

• Firewall Management (Palo Alto, Checkpoint):

o Configure and maintain Palo Alto and Checkpoint firewalls to ensure network security and integrity

o Monitor firewall performance, implement policy changes, and respond to any security incidents or alerts.

Required Skills and Qualifications:

• Proven experience in managing and configuring Cisco wireless infrastructure, switches, and routers.

• Strong knowledge and hands-on experience with SolarWinds network monitoring tool.

• Proficiency in managing Palo Alto and Checkpoint firewalls.

• Strong troubleshooting skills for network and security-related issues.

• Ability to perform firmware upgrades for network devices and equipment.

• Familiarity with network security practices and protocols.

• CCNP (Cisco Certified Network Associate) certification or equivalent is a plus.

• Experience with network documentation and creating network diagrams.

Preferred Skills:

• Advanced Cisco certifications (CCNP) or equivalent.

• Knowledge of other network security platforms.

• Experience in implementing network automation or orchestration tools.

We are seeking a skilled and motivated Data Engineer with expertise in Hadoop, Spark, OpenShift Container Platform (OCP), and DevOps practices. As a Data Engineer, you will be responsible for designing, developing, and maintaining efficient data pipelines, processing large-scale datasets. Your expertise in Hadoop, Spark, OCP, and DevOps will be crucial in ensuring the availability, scalability, and reliability of our ML Solutions.

Responsibilities:

• Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives
• Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions
• Ensure data quality and integrity throughout the data processing lifecycle
• Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques
• Optimize data engineering workflows for containerized deployment and efficient resource utilization
• Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability
• Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance
• Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements
• Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference
• Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps
• Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities within the bank

• Bachelor's degree in Computer Science, Information Technology, or a related field
• Proven 2-5 Years of experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments
• trong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
• Experience with Graphana, Prometheus, Splunk will be an added benefit
• trong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges
• Excellent collaboration and communication skills to work effectively with cross-functional teams
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus

As a Lead Data Engineer, you will play a leading role in designing, building, and optimizing our data infrastructure, ensuring that it supports the advanced analytics need of the bank. You will oversee a team of data engineers, working closely with data analysts, DevOps team, infrastructure engineers, and other stakeholders to deliver high-quality data solution.

Your main responsibilities will include:

• Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data.
• Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data.
• Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch.
• Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions.
• Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques.
• Optimize data engineering workflows for containerized deployment and efficient resource utilization.
• Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability.
• Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements.
• Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure.
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference.
• Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps.
• Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities within the bank.

• Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field.
• At least 10 years of experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments.
• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Ranger, etc)
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes.
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java.
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
• Experience with Grafana, Prometheus, Splunk will be an added benefit
• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges.
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus.

We are seeking a skilled and motivated Data Engineer with expertise in Hadoop, Spark, OpenShift Container Platform (OCP), and DevOps practices. As a Data Engineer, you will be responsible for designing, developing, and maintaining efficient data pipelines, processing large-scale datasets. Your expertise in Hadoop, Spark, OCP, and DevOps will be crucial in ensuring the availability, scalability, and reliability of our ML Solutions.

Your main responsibilities will include:

• Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives
• Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions
• Ensure data quality and integrity throughout the data processing lifecycle
• Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques
• Optimize data engineering workflows for containerized deployment and efficient resource utilization
• Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability
• Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance
• Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements
• Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference
• Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps
• Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities within the bank

• ·Bachelor's degree in Computer Science, Information Technology, or a related field
• Proven experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments
• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
• Experience with Graphana, Prometheus, Splunk will be an added benefit
• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenge
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment

We are seeking a talented and experienced Senior Data Engineer (Quantexa)with expertise in Hadoop, Scala, Spark, Elastic, Open Shift Container Platform (OCP) and DevOps practices. Elasticsearch to join our team. As a Data Engineer, you will play a crucial role in designing, developing, and optimizing big data solutions using Apache Spark, Scala, and Elasticsearch. You will collaborate with cross-functional teams to build scalable and efficient data processing pipelines and search applications. Knowledge and experience in the Compliance / AML domain will be a plus. Working experience with Quantexa tool is a must.

Responsibilities:

·        Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives

·        Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions

·        Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data

·        Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data

·        Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch

·        Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch

·        Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards

·        Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration

·        Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components

·        Ensure data quality and integrity throughout the data processing lifecycle

·        Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques

·        Optimize data engineering workflows for containerized deployment and efficient resource utilization

·        Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability

·        Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance

·        Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements

·        Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure

·        Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference

1. More than 5 years of experience as a Data Engineer
2. · Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline
3. · Possession of Quantexa certification as a Data Engineer or Data Architect, with proficiency in the tool
4. · Demonstrated experience as a Data Engineer, utilizing Hadoop, Spark, and data processing technologies in large-scale environments
5. · Expertise in the Scala programming language and familiarity with functional programming principles
6. · Prior experience with the Quantexa tool is highly desirable
7. · Comprehensive understanding of Apache Spark architecture, including RDDs, DataFrames, and Spark SQL
8. · Advanced proficiency in designing and developing data infrastructure utilizing Hadoop, Spark, and associated tools (HDFS, Hive, Pig, etc.)
9. · Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration via Kubernetes
10. · Proficiency in programming languages commonly employed in data engineering, including Spark, Python, Scala, or Java
11. · Knowledge of DevOps methodologies, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
12. · Experience with Graphana, Prometheus, and Splunk will be considered an added advantage
13. · Background in integrating and utilizing Elasticsearch for data indexing and search applications
14. · Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization techniques
15. · Experience with distributed computing, parallel processing, and handling large datasets
16. · Proficient in performance tuning and optimization methods for Spark applications and Elasticsearch queries
17. · Strong problem-solving and analytical capabilities with the capacity to debug and resolve intricate issues
18. · Familiarity with version control systems (e.g., Git) and collaborative development environments

We are looking for a talented Software Engineer with strong expertise in Python, Shell Scripting, Unix, and Automation. The ideal candidate is a self-starter who thrives in a fast-paced environment and can join immediately to contribute to mission-critical projects.

Key Responsibilities:

• Develop, test, and maintain Python scripts for automation and application development.
• Create and manage Shell Scripts for process automation and system management.
• Perform system administration and maintenance on Unix/Linux platforms.
• Design and implement automation workflows to streamline operations.
• Collaborate with cross-functional teams to gather and analyze requirements.
• Troubleshoot and resolve technical issues promptly.
• Ensure the security, reliability, and scalability of automated solutions.

• Min 5+ Years of experience as Software Developer
• Proficiency in Python programming, with a focus on scripting and automation.
• Strong knowledge of Shell Scripting
• Hands-on experience with Unix systems.
• Familiarity with automation tools and frameworks.
• Strong problem-solving and analytical abilities.
• Immediate joiner preferred

• Assist in the development and optimization of ETL processes using PySpark and Databricks.
• Collaborate with team members to design and implement data models and architecture in AWS.
• Maintain and monitor data pipelines to ensure data quality and reliability.
• Utilize GitHub for version control and collaboration on codebases.
• Participate in code reviews and contribute to best practices in coding and data engineering.
• Support the team in implementing CI/CD practices for data workflows.
• Document processes and workflows for data engineering tasks.

• Familiarity with AWS services (e.g., S3, Redshift, Glue) and cloud computing concepts.
• Basic knowledge of Databricks and PySpark for data processing.
• Understanding of Git and experience with GitHub for version control.
• Awareness of DevOps principles and tools (e.g., CI/CD, Docker) is a plus.
• Databricks certification is a plus.

• Design, develop, and maintain scalable data pipelines and ETL processes using Hadoop and Spark.
• Write efficient and optimized data processing jobs in Scala to transform and load data.
• Utilize SQL for querying and manipulating data across various databases.
• Collaborate with data scientists and analysts to gather requirements and deliver data solutions that meet business needs.
• Monitor and troubleshoot data processing workflows to ensure high performance and reliability.
• Implement best practices for data quality, governance, and security.
• Document data engineering processes, workflows, and architecture for team knowledge sharing.
• Stay updated on industry trends and emerging technologies to continuously improve our data strategies.

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a Data Engineer or in a similar role.
• Strong proficiency in Hadoop ecosystem components (e.g., HDFS, Hive, Pig).
• Hands-on experience with Apache Spark for big data processing.
• Proficient in Scala programming for data transformation tasks.
• Advanced SQL skills for querying and managing large datasets.
• Experience with data modeling, data warehousing, and ETL processes.
• Familiarity with cloud platforms (AWS, GCP, or Azure) is a plus.
• Strong analytical and problem-solving skills.

We are seeking an experienced Data Engineer with a strong background in Hadoop, Spark, and SQL, specifically within the banking sector. The ideal candidate will be responsible for designing, building, and maintaining large-scale data pipelines and platforms to support critical banking applications and decision-making processes.

Key Responsibilities:

• Data Pipeline Development: Design, develop, and maintain efficient data pipelines and workflows using Hadoop and Spark frameworks to support the bank’s data processing needs.
• Data Integration & ETL: Create ETL processes to extract, transform, and load large datasets into Hadoop ecosystems from various banking systems, ensuring data consistency and accuracy.
• Database Management: Write optimized SQL queries to manage and analyze data stored across relational databases, data lakes, and cloud platforms.
• Data Processing & Analysis: Implement scalable data processing solutions to analyze large datasets, provide insights, and deliver solutions for financial services and risk management.
• Collaboration: Work closely with business analysts, data scientists, and IT teams to ensure data solutions align with banking sector needs, including compliance with regulations and reporting requirements.
• Performance Optimization: Fine-tune Hadoop and Spark applications for performance, improving throughput and reducing latency.

• Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
• Strong years  experience as a Data Engineer, specifically within the banking or financial sector.
• Proficiency in Hadoop ecosystem tools (HDFS, Hive, HBase) and Spark for large-scale data processing.
• Strong experience with SQL and relational databases such as PostgreSQL, MySQL, or Oracle.
• Familiarity with cloud platforms (AWS, Azure) and containerization tools (Docker, Kubernetes) is a plus.
• Experience in data governance and compliance regulations within the financial industry.
• Excellent problem-solving and analytical skills.

• Salary: SGD 6000 - 9500
• Great Work Culture
• Includes comprehensive insurance for self and family. Includes Specialist and Dental Coverage.
• Includes Standard Annual and Sick Leave

• Analyse the Authority’s data needs and document the requirements.
• Refine data collection/consumption by migrating data collection to more efficient channels.
• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.
• Develop test plan and scripts for system testing, support user acceptance testing.
• Work with the Authority’s technical teams to ensure smooth deployment and adoption of new solution.
• Ensure the smooth operations and service level of IT solutions.
• Support production issues.
• Good understanding and completion of projects using waterfall/Agile methodology.
• Hands-on experience in DevOps deployment and data virtualisation tools like Denodo will be preferred.
• Understanding of reporting or visualization tool like SAP BO and Tableau is important.
• Track record in implementing systems using Hive, Impala and Cloudera Data Platform will be preferred.
• Hands-on experience in big data engineering jobs using Python, Pyspark, Linux, and ETL tools like Informatica.
• Strong SQL and data modelling and data analysis skills.
• Good understanding of analytics and data warehouse implementations.
• Ability to troubleshoot complex issues ranging from system resource to application stack traces.
• Track record in implementing systems with high availability, high performance, high security hosted at various data centres or hybrid cloud environments will be an added advantage.

As a Data Engineer specializing in Data Mapping & ETL, you will play a crucial role in designing and implementing data solutions that ensure efficient and accurate data movement across systems. Your responsibilities will include:

• Developing and maintaining ETL processes for data extraction, transformation, and loading.
• Conducting data mapping to transform data across multiple systems and formats.
• Collaborating with data architects and other stakeholders to understand data requirements.
• Optimizing ETL processes for performance and reliability.
• Conducting data quality assessments and implementing data validation techniques.
• Documenting ETL processes and best practices for future reference.

This role will require a blend of technical expertise and analytical skills to manage complex data flows effectively.

To be successful in this role, you should meet the following requirements:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 4+ years of experience in ETL development and data mapping.
• Strong proficiency in SQL and experience with databases such as Oracle, Postgres, or SQL Server.
• Experience with ETL tools such as Apache NiFi, Talend, or AWS Glue.
• Familiarity with data warehousing concepts and dimensional modeling.
• Knowledge of data quality frameworks and data governance principles.
• Proficient in scripting languages like Python or Shell.
• Ability to work in an Agile environment and collaborate with cross-functional teams.
• Preferred : Immediate joiner or max 1 Month

• Design, implement, and maintain ETL processes to extract data from multiple sources, transform it based on business rules, and load it into target systems.
• Develop and manage data mapping documentation, including source-to-target mappings and transformation logic.
• Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and optimize data flows.
• Conduct data quality checks and validation to ensure the accuracy and integrity of data.
• Optimize ETL workflows for performance, scalability, and reliability.
• Monitor and troubleshoot ETL processes, resolving issues promptly to minimize downtime.
• Stay up-to-date with industry best practices and emerging technologies in data engineering and ETL.

• Proven experience as a Data Engineer, with a strong focus on data mapping and ETL processes.
• Strong SQL skills and experience with relational databases (e.g., MySQL, PostgreSQL, Oracle).
• Familiarity with data warehousing concepts and architecture.

Key Responsibilities:

·        Develop and maintain the user interface using React/UI for a seamless user experience.

·        Work with Python (preferred) or Java for backend development.

·        Handle email communication systems using SMTP.

·        Design and implement APIs using Swagger, REST, or SOAP protocols.

·        Manage the server-side environment with expertise in Unix/Linux.

·        Log and monitor applications using Elastic logging (ELK).

·        Work with databases like MongoDB or PostgreSQL for efficient data management.

·        Utilize Postfix for managing email services and configurations.

·        Collaborate with teams to ensure software aligns with banking/financial industry requirements.

Skills Required:

·        Front-End: React/UI

·        Back-End: Python or Java

·        SMTP, API Development (Swagger, REST, SOAP)

·        Unix/Linux experience required

·        ELK Stack (Elastic Logging)

·        Database: MongoDB or PostgreSQL

·        Postfix

·        Functional Understanding of Banking/Financial Systems

• Analyze, design, program, test, document and maintain IT systems or applications
• Provide maintenance support to customers (internal and/or external) by investigating and rectifying reported systems shortcomings.
• Analyze requests for enhancements/changes and write amendment/program specifications.
• Update system documentation.
• Perform and manage stages of the SDLC and participate in the systems review with Project Lead/Manager.
• Understand the interdependencies of the services (application, system and database) and able to pin-point problem areas accurately to improve overall efficiency.
• Design and document system design, architecture and propose appropriate technologies and tools required to implement systems; and ensure users sign-off on design specifications.
• Use development tools to develop applications for better productivity.
• Develop test cases, conduct SIT, load test and tune the performance of systems to meet SLA.
• Deploy systems to production and provide post-implementation support.
• Provide technical guidance to junior colleagues in their work.
• Keep abreast of technological advancement, emerging standards and new software or hardware solutions that may affect decisions about system builds or enhancements.
• Any other duties as and when assigned.

Requirements:

• Experienced in developing enterprise web applications and web services.

• Experienced in developing mobile applications is advantageous.

• Experienced with Agile methodology is advantageous.

• Microsoft related certifications are advantageous.

• Technical Skills Requirement

o Mandatory Skills

 HTML5, CSS3, JavaScript, jQuery, Bootstrap

 C#, .NET Framework 4.x, .NET MVC 3 and above, Entity Framework 6.x

 RESTful APIs, JSON

 SQL

o Mandatory Tools

 NET CORE 3.1 and above (Ideally)

 Visual Studio 2015 and above.

 MS SQL Server 2012 and above.

o Good to have

 Single Sign-On (e.g. OAuth, etc.)

 React JS

o Optional Skills

 Telerik, Kendo UI

 Team Foundation Services (TFS) or Visual Studio Team Services (VSTS).

 SQL Server Reporting Services (SSRS).

 SQL Server Integration Services (SSIS).

 Microsoft Azure

We are seeking a skilled and motivated Data Engineer with expertise in Hadoop, Spark, OpenShift Container Platform (OCP), and DevOps practices. As a Data Engineer, you will be responsible for designing, developing, and maintaining efficient data pipelines, processing large-scale datasets. Your expertise in Hadoop, Spark, OCP, and DevOps will be crucial in ensuring the availability, scalability, and reliability of our ML Solutions.

Responsibilities:

•  Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives
• Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions
• Ensure data quality and integrity throughout the data processing lifecycle
• Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques
• Optimize data engineering workflows for containerized deployment and efficient resource utilization
• Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability
• Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance
• Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements
• Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure
• Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference
• Stay updated with emerging technologies, industry trends, and best practices in data engineering and DevOps
• Provide technical leadership, mentorship, and guidance to junior team members to foster a culture of continuous learning and innovation to the continuous improvement of the analytics capabilities .

• Proven 4+ Years of experience as a Data Engineer, working with Hadoop, Spark, and data processing technologies in large-scale environments
• Strong expertise in designing and developing data infrastructure using Hadoop, Spark, and related tools (HDFS, Hive, Pig, etc)
• Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration using Kubernetes
• Proficiency in programming languages commonly used in data engineering, such as Spark, Python, Scala, or Java
• Knowledge of DevOps practices, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
• Experience with Graphana, Prometheus, Splunk will be an added benefit
• Strong problem-solving and troubleshooting skills with a proactive approach to resolving technical challenges
• Ability to manage multiple priorities, meet deadlines, and deliver high-quality results in a fast-paced environment
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and their data services is a plus

We are seeking a talented and experienced Data Engineer (Quantexa)with expertise in Hadoop, Scala, Spark, Elastic, Open Shift Container Platform (OCP) and DevOps practices. Elasticsearch to join our team. As a Data Engineer, you will play a crucial role in designing, developing, and optimizing big data solutions using Apache Spark, Scala, and Elasticsearch. You will collaborate with cross-functional teams to build scalable and efficient data processing pipelines and search applications. Knowledge and experience in the Compliance / AML domain will be a plus. Working experience with Quantexa tool is a must.

Responsibilities:

·        Implement data transformation, aggregation, and enrichment processes to support various data analytics and machine learning initiatives

·        Collaborate with cross-functional teams to understand data requirements and translate them into effective data engineering solutions

·        Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data

·        Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data

·        Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch

·        Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch

·        Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards

·        Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration

·        Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components

·        Ensure data quality and integrity throughout the data processing lifecycle

·        Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques

·        Optimize data engineering workflows for containerized deployment and efficient resource utilization

·        Collaborate with DevOps teams to streamline deployment processes, implement CI/CD pipelines, and ensure platform stability

·        Implement data governance practices, data lineage, and metadata management to ensure data accuracy, traceability, and compliance

·        Monitor and optimize data pipeline performance, troubleshoot issues, and implement necessary enhancements

·        Implement monitoring and logging mechanisms to ensure the health, availability, and performance of the data infrastructure

·        Document data engineering processes, workflows, and infrastructure configurations for knowledge sharing and reference

1. More than 5 years of experience as a Data Engineer
2. · Bachelor's or Master's degree in Computer Science, Software Engineering, or a related discipline
3. · Possession of Quantexa certification as a Data Engineer or Data Architect, with proficiency in the tool
4. · Demonstrated experience as a Data Engineer, utilizing Hadoop, Spark, and data processing technologies in large-scale environments
5. · Expertise in the Scala programming language and familiarity with functional programming principles
6. · Prior experience with the Quantexa tool is highly desirable
7. · Comprehensive understanding of Apache Spark architecture, including RDDs, DataFrames, and Spark SQL
8. · Advanced proficiency in designing and developing data infrastructure utilizing Hadoop, Spark, and associated tools (HDFS, Hive, Pig, etc.)
9. · Experience with containerization platforms such as OpenShift Container Platform (OCP) and container orchestration via Kubernetes
10. · Proficiency in programming languages commonly employed in data engineering, including Spark, Python, Scala, or Java
11. · Knowledge of DevOps methodologies, CI/CD pipelines, and infrastructure automation tools (e.g., Docker, Jenkins, Ansible, BitBucket)
12. · Experience with Graphana, Prometheus, and Splunk will be considered an added advantage
13. · Background in integrating and utilizing Elasticsearch for data indexing and search applications
14. · Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization techniques
15. · Experience with distributed computing, parallel processing, and handling large datasets
16. · Proficient in performance tuning and optimization methods for Spark applications and Elasticsearch queries
17. · Strong problem-solving and analytical capabilities with the capacity to debug and resolve intricate issues
18. · Familiarity with version control systems (e.g., Git) and collaborative development environments

We are looking for a motivated and innovative Software Engineer with a passion for Machine Learning and Artificial Intelligence. This role is ideal for fresh graduates with a solid foundation in Python programming and an eagerness to work on AI-driven solutions. You will be a part of a collaborative team developing intelligent systems and applications that solve real-world problems.

Key Responsibilities:

• Develop, test, and deploy scalable software applications using Python.
• Collaborate with data scientists and AI researchers to build machine learning models and integrate them into production systems.
• Write efficient code to implement AI algorithms, automating data processes, and deploying AI models.
• Assist in developing machine learning pipelines, data pre-processing, feature extraction, and model training.
• Analyze and optimize machine learning algorithms for performance and scalability.
• Participate in code reviews, design discussions, and system architecture planning.
• Work closely with the product development team to translate requirements into technical solutions.
• Stay up-to-date with the latest trends and advancements in AI and machine learning.

Educational Background: Bachelor’s degree in Computer Science, Information Technology, Data Science, or a related field.

Programming Skills: Proficiency in Python; experience with libraries such as NumPy, pandas, scikit-learn, TensorFlow, or PyTorch is a plus.

Machine Learning Knowledge: Familiarity with machine learning algorithms and frameworks.

AI Experience: Basic understanding of AI concepts and how they are applied to real-world problems.

Database Skills: Experience with SQL and NoSQL databases is an advantage.

Analytical Thinking: Strong problem-solving skills with attention to detail.

• Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data
• Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data
• Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch
• Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions
• Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch
• Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards
• Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration

1. 5+ Years as Data Engineer
2. 5 Years experience in Spark, Scala, Elastic Search
3. Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards
4. Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components
5. Stay updated with emerging trends and advancements in the big data technologies space to ensure continuous improvement and innovation
6. Mandatory Skills : Spark, Scala & Elastic Search

We are seeking experienced Software Engineers proficient in Java to join our dynamic team. The ideal candidates will have hands-on experience in containers, cloud platforms, and distributed systems.

Key Responsibilities:

• Develop, test, and deploy scalable Java applications.
• Design and manage containerized applications using Docker and Kubernetes.
• Leverage cloud services (Azure, AWS, GCP) for application deployment and maintenance.
• Implement distributed systems and ensure high availability and performance.
• Collaborate with cross-functional teams to deliver high-quality software solutions.
• Troubleshoot and resolve complex technical issues.
• Stay updated with industry trends and integrate best practices.
• Participate in code reviews and contribute to continuous improvement.

Strong experience in Java, J2EE, and related technologies.

Proficiency in containerization and cloud platforms.

Knowledge of distributed systems architecture.

Responsibilities:

• Design and implement database solutions based on business requirements
• Optimize and tune database performance by analyzing query execution plans and identifying bottlenecks
• Ensure data integrity and security by implementing backup and recovery strategies
• Collaborate with cross-functional teams to troubleshoot and resolve database-related issues
• Perform database capacity planning and implement scaling strategies
• Monitor database systems to identify potential issues and proactively address them

Requirements:

• Bachelor's degree in Computer Science or related field
• Proven experience as a Database Engineer or similar role
• In-depth knowledge of database management systems, such as MySQL, PostgreSQL, or Oracle
• Strong understanding of database performance tuning and optimization techniques
• Experience with database backup and recovery procedures
• Familiarity with database security best practices
• Excellent problem-solving and troubleshooting skills
• Ability to work well in a team environment
• Strong communication skills

• Salary: SGD 6000 - 12000
• Great Work Culture
• Includes comprehensive insurance for self and family. Includes Specialist and Dental Coverage.
• Includes Standard Annual and Sick Leave

We are seeking a talented and experienced Spark Scala Developer with expertise in Elasticsearch to join our team. As a Spark Scala Developer, you will play a crucial role in designing, developing, and optimizing big data solutions using Apache Spark, Scala, and Elasticsearch. You will collaborate with cross-functional teams to build scalable and efficient data processing pipelines and search applications. Knowledge and experience in the Compliance / AML domain will be a plus.

•           Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data

•           Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data

•           Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch

•           Collaborate with data engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions

•           Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch

•           Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards

•           Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration

•           Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components

•           Stay updated with emerging trends and advancements in the big data technologies space to ensure continuous improvement and innovation

•           Strong experience in developing Spark applications. Experience with Spark Streaming is a plus

•           Proficiency in Scala programming language and familiarity with functional programming concepts

•           In-depth understanding of Apache Spark architecture, RDDs, DataFrames, and Spark SQL

•           Experience integrating and working with Elasticsearch for data indexing and search applications

•           Solid understanding of Elasticsearch data modeling, indexing strategies, and query optimization

•           Experience with distributed computing, parallel processing, and working with large datasets

•           Familiarity with big data technologies such as Hadoop, Hive, and HDFS

•           Proficient in performance tuning and optimization techniques for Spark applications and Elasticsearch queries

•           Strong problem-solving and analytical skills with the ability to debug and resolve complex issues

•           Familiarity with version control systems (e.g., Git) and collaborative development workflows

•           Excellent communication and teamwork skills with the ability to work effectively in cross-functional teams

We are seeking a skilled and motivated Data Engineer with expertise in Google Cloud Platform tools such as BigQuery, Composer, Dataproc, and ETL processes. The ideal candidate will have a strong background in designing, implementing, and optimizing data pipelines and workflows. You will play a key role in ensuring our data infrastructure is scalable, efficient, and reliable to support our data-driven decision-making processes.

Key Responsibilities:

• Design and Development:
• Develop, construct, test, and maintain scalable data pipelines using Big Query, Composer, Dataproc, and other GCP tools.
• Design and implement ETL processes to extract, transform, and load data from various sources into the data warehouse.
• Ensure the architecture supports business requirements and allows for easy reporting and analysis.
• Data Management:
• Monitor and manage data workflows and pipelines to ensure data quality, integrity, and reliability.
• Perform data profiling and analysis to identify and address data quality issues.
• Optimization and Performance:
• Optimize ETL processes and data pipeline performance to handle large-scale data efficiently.
• Implement best practices for data governance, security, and compliance.
• Collaboration
• Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions.
• Troubleshooting and Support:
• Identify, diagnose, and resolve data-related issues and discrepancies.
• Provide support and troubleshooting for data pipelines and ETL processes.

Minimum of 5 years of experience as a Data Engineer or in a similar role.

Proven experience with Google Cloud Platform, specifically Big Query, Composer, Dataproc, and GCP Tools.

Strong experience with ETL processes and tools.

• Analyze the Authority’s data needs and document the requirements.

• Refine data collection/consumption by migrating data collection to more efficient channels.

• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.

• Develop test plan and scripts for system testing, support user acceptance testing.

• Work with the Authority’s technical teams to ensure smooth deployment and adoption of new solution.

• Ensure the smooth operations and service level of IT solutions.

• Support production issues - Track record in implementing systems with high availability, high performance, high security.

• Good understanding and completion of projects using waterfall/Agile methodology.

• Good understanding of analytics and data warehouse implementations.

• Ability to troubleshoot complex issues ranging from system resource to application stack traces.

• Strong SQL, data modelling and data analysis skills are a must.

• Hands-on experience in big data engineering jobs using Python, PySpark, Linux, and ETL tools like Informatica.

• Track record in implementing systems using Hive, Impala and Cloudera Data Platform will be preferred.

• Hands-on experience in DevOps deployment and data virtualization tools like Denodo will be preferred.

• Understanding/ Hands on experience of reporting or visualization tool like SAP BO and Tableau will be beneficial but not required.

• Passion for automation, standardization, and best practices

• Good written and verbal communication and interpersonal skills, ability to understand the business requirement, communicate confidently with stakeholders.

• Analyze, design, program, test, document and maintain IT systems or applications
• Provide maintenance support to customers (internal and/or external) by investigating and rectifying reported systems shortcomings.
• Analyze requests for enhancements/changes and write amendment/program specifications.
• Update system documentation.
• Perform and manage stages of the SDLC and participate in the systems review with Project Lead/Manager.
• Understand the interdependencies of the services (application, system and database) and able to pin-point problem areas accurately to improve overall efficiency.
• Design and document system design, architecture and propose appropriate technologies and tools required to implement systems; and ensure users sign-off on design specifications.
• Use development tools to develop applications for better productivity.
• Develop test cases, conduct SIT, load test and tune the performance of systems to meet SLA.
• Deploy systems to production and provide post-implementation support.
• Provide technical guidance to junior colleagues in their work.
• Keep abreast of technological advancement, emerging standards and new software or hardware solutions that may affect decisions about system builds or enhancements.
• Any other duties as and when assigned.
• Bachelor’s degree in Computer Science, IT or related fields
• Experienced in developing enterprise web applications and web services.
• Experienced in developing mobile applications is advantageous.
• Experienced with Agile methodology is advantageous.
• Microsoft related certifications are advantageous.
• This role requires to provide "24/7" on call support, deployment activities on weekends and public holidays.

Technical Skills Requirement

Mandatory Skills

• HTML5, CSS3, JavaScript, jQuery, Bootstrap
• C#, .NET Framework 4.x, .NET MVC 3 and above, Entity Framework 6.x
• RESTful APIs, JSON
• SQL
• NET CORE 1.1 and above (Ideally)
• Visual Studio 2015 and above.
• MS SQL Server 2012 and above.
• Good to have
• React JS

We are looking for a skilled Data Engineer with a strong background in Python, PySpark, Spark, and SQL. The ideal candidate will have experience in building and optimizing data pipelines and architectures. This role requires a collaborative professional who can work across teams to design and implement robust data solutions.

Key Responsibilities:

• Design, build, and maintain efficient, scalable, and reliable data pipelines using Python, PySpark, Spark, and SQL.
• Collaborate with data scientists, analysts, and other stakeholders to understand data needs and deliver appropriate data solutions.
• Develop and optimize ETL (Extract, Transform, Load) processes to ensure data quality and integrity.
• Implement data processing workflows for batch and real-time data integration.
• Monitor and troubleshoot data pipelines, ensuring data accuracy and availability.
• Perform data exploration and analysis to support business decisions.
• Document data processes, architectures, and workflows.

Proven 4+Years of experience as a Data Engineer or in a similar role.

Strong proficiency in Python and PySpark for data manipulation and transformation.

Hands-on experience with Apache Spark for large-scale data processing.

Advanced SQL skills for data querying, transformation, and performance tuning.

Familiarity with cloud platforms (AWS, Azure, Google Cloud) and their data services.

Experience with data warehousing concepts and technologies (e.g., Redshift, BigQuery, Snowflake).

Knowledge of best practices for data architecture and data governance.