Total 95 job vacancies by Unison Consulting Pte. Ltd.

• We are seeking an experienced SOFTWARE ENGINEER with required experince with expertise in C, C++, Linux, Unix, and integration tools like JSON, SOAP, XML.
• The ideal candidate will work on Oracle Tuxedo platform, handling system integration and application development. Proficiency in Linux/Unix environments, SQL, and hands-on experience in Pro*C programming is essential.
• Strong problem-solving skills and a solid understanding of middleware integration are required.
• Join us for a challenging role in a dynamic environment focusing on critical systems.

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

Job Summary:

We are looking for a strong DevOps candidate to join our DevOps team which manages our DevSecOps infrastructure and works with application teams to automate software deployments. Other than BAU work, the team also works on projects to enhance, optimize and transform the infrastructure.

Key Responsibilities:

• Coding and developing new DevOps scripts automation with CI/CD pipelines through Jenkins, Cloudbees, Bitbucket, etc

• Supporting and maintaining full stack DevOps toolsets. (Jira, Confluence, Bitbucket, Cloudbees, Jenkins, SonarQube, Nexus IQ, Fortify )

• Able to code, script, automate, innovate full DevOps automation capabilities to enhance and elevate automation from manual human tasks

• Always able to find ways to automate, develop scripts, innovate new ideas to reduce human work and repetitive tasks.

• Deep knowledge on DevOps tools API automation capabilities.

• Troubleshoot, deep dive RCA and fix DevOps platform issues.

• Supporting DevOps toolsets running on AWS, container clusters and Kubernetes.

What we are looking for:

• Deep experience as a DevOps or DevSecOps practitioner in a critical Production environment

• Deep technical experience in server-side Unix/Linux/PowerShell scripting

• Prior working experience installing, configuring, integrating, upgrading and patching CI/CD toolset

• Prior experience is customizing JIRA and Setting up confluence spaces.

• Passionate about cloud infrastructure, CI/CD pipelines and automation

• Ability to easily pick up new technologies: you are keen to learn and to expand your knowledge

• Customer centricity: you always go above and beyond to deliver a first-class service to your users

• Highly proficient with Linux Systems Administration and network fundamentals (IPv4, TCP, UDP, DNS, HTTP, TLS, routing, load-balancing)

• Proficient with AWS VPC, EC2, IAM, S3, EKS, EFS

• Proficient with ELK, Grafana and Ansible

• Proficient with Terraform, Docker/containers and Kubernetes

• 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

• In-charge of on-premise / Cloud virtual Solaris and Linux servers administration and managing the physical servers in Data Centre.
• Responsible for installation, configuration and maintenance of UNIX and Linux operating systems and all related systems and software.
• Responsible for working in WebLogic and support operational perspective of managing web logic software.
• In depth knowledge in Unix and Linux Server OS administration to install, configures and maintain by regular patching to ensure system stability and secure.
• Well versed in security hardening and security fixes and have involved in security VA remediation analysis and execution which performed regularly in project environment.
• Experienced and proficient to provide advanced level support for new installation, configuration, and troubleshooting.
• Hands-on experienced in configuring, administering, and troubleshooting on Unix or Linux clustering environment.
• Manage storage infrastructure IBM flash system family and Dell - EMC storage family with zoning administration.
• Have basic knowledge of to install, configure and support Weblogic, OHS middleware components installed on Unix and Linux.
• Have worked or experience on KVM virtualization platform and VMware ESXi environment.
• Familiarity with, UNIX, and LINUX shell scripting
• Understanding of backup and recovery procedures using backup tools for e.g. NetBackup.

Minimum 4-9 years of experience in managing Unix/Linux and Middleware platform with specializing skills listed below:

1. Solaris 10 and 11, AWS or Azure.

2. Oracle Linux and RedHat

3. Oracle LDOM Virtualization

4. Veritas NetBackup

5. Trend Micro Deep Security

6. WebLogic 11g,12C, OHS 11g, 12c, Oracle LDAP

7. OHS 11g, 12c

8. Sun Cluster and Veritas storage foundation

9. Storage IBM/DELL-EMC

We are looking for a strong DevOps candidate to join our DevOps team which manages our DevSecOps infrastructure and works with application teams to automate software deployments. Other than BAU work, the team also works on projects to enhance, optimize and transform the infrastructure.

Key Responsibilities

• Coding and developing new DevOps scripts automation with CI/CD pipelines through Jenkins, Cloudbees, Bitbucket, etc

• Supporting and maintaining full stack DevOps toolsets. (Jira, Confluence, Bitbucket, Cloudbees, Jenkins, SonarQube, Nexus IQ, Fortify)

• Able to code, script, automate, innovate full DevOps automation capabilities to enhance and elevate automation from manual human tasks

• Always able to find ways to automate, develop scripts, innovate new ideas to reduce human work and repetitive tasks.

• Deep knowledge on DevOps tools API automation capabilities

• Troubleshoot, deep dive RCA and fix DevOps platform issues

• Supporting DevOps toolsets running on AWS, container clusters and Kubernetes.

What we are looking for

• Deep experience as a DevOps or DevSecOps practitioner in a critical Production environment
• Deep technical experience in server-side Unix/Linux/PowerShell scripting
• Prior working experience installing, configuring, integrating, upgrading and patching CI/CD toolset
• Prior experience is customizing JIRA and Setting up confluence spaces.
• Passionate about cloud infrastructure, CI/CD pipelines and automation
• Ability to easily pick up new technologies: you are keen to learn and to expand your knowledge
• Customer centricity: you always go above and beyond to deliver a first-class service to your users
• Highly proficient with Linux Systems Administration and network fundamentals (IPv4, TCP, UDP, DNS, HTTP, TLS, routing, load-balancing)
• Proficient with AWS VPC, EC2, IAM, S3, EKS, EFS
• Proficient with ELK, Grafana and Ansible
• Proficient with Terraform, Docker/containers and Kubernetes

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

As a Lead ML Engineer, you will play a leading role in operationalizing ML Models developed by Client data scientists. You will serve as the focal point for ML model refactoring, optimization, containerization, deployment, and quality monitoring. Your main responsibilities will include:

• Conduct reviews for compliance of the ML models in accordance with overall platform governance principles such as versioning, data / model lineage, code best practices and provide feedback to data scientists for potential improvements
• Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain. This can include monitoring for data drift, triggering model retraining and setting up rollbacks.
• Optimize AI development environments (development, testing, production) for usability, reliability and performance.
• Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications (e.g., transforming resulting models into APIs).
• Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines feeding these repositories and the ML feature or data stores are working as intended.
• Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.

Technical Skills

• At least 10 years of experience as a ML Engineer, working with Python, ML libraries, and large-scale data processing framework.
• Advance proficiency in Python used both for ML and automation tasks.
• Experience in working with ML libraries such as Panda, NumPy, H2O, or TensorFlow.
• Experience in working with large-scale data processing framework, such as Hadoop, Spark, or Dask.
• Knowledge of OpenShift / Kubernetes is a must-have.
• Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Knowledge in the operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g., Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, Dataiku, H2O, or DKube).
• Knowledge of Workflow Orchestrator, such as Airflow or Ctrl-M.
• Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
• Experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
• Experience in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms.
• Knowledge of cloud platforms (e.g. AWS, GCP) would be an advantage.

We seek individuals with highly developed conceptual, strategic, and analytical skills, capable of striking a balance between visionary thinking and practical solutions. The ability to comprehend, inspire, and mobilize others is crucial. A business-oriented mindset coupled with effective storytelling will drive your success. We are looking for self-starters ready to take on responsibilities with enthusiasm.

• Developing and maintaining the entire DevOps pipelines.
• Coordinate with the stakeholders from requirements gathering until successful implementation DevOps pipeline on boarding.
• Work with the vendors and for internal platforms to setup centralized DevOps solutions considering market best practice, Industry standard and ease of support.
• Work with the vendors and for internal platforms to upgrade the DevOps tools farm and integrating with tools.
• Lead analysis and resolution of root cause for Test Orchestration / Environment related issues
• Ability to multitask and work in a fast-paced, collaborative team environment.
• Stays current with industry trends and leads development of key DevOps, Runtime, and Operational innovation platforms

• Deep technical background, with hands-on experience in supporting CI/CD pipelines (Bitbucket, Jenkins, Artifactory, Sonar, Veracode for SAST, JIRA and Confluence).
• Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
• Skill to containerize a application and good if Kubernetes
• Good Experience on OpenShift or AWS
• Prior technical background on different build and branching strategies.
• Deep technical background on Kubernetes deployment process.
• Good knowledge on maintaining/deploying secrets in Kubernetes.
• Prior working experience in setting up Jira workflow.
• Strong hands-on experience on Shell or Groovy scripting.
• Prior experience is customizing JIRA and Setting up confluence spaces.
• Prior hand-on experience in setting up CI/CD pipeline as a centralized solution.
• Hand on experience in setting up DevOps governance, Security standards and audit requirements.
• Prior experience in setting up DevOps pipeline in internal and external cloud offerings.
• Experience with continuous testing, techniques and tools (Junit, Sonar Cube, Veracode etc.)
• Technical exposure of automation accomplished with advanced Python, Chef, Ruby and PowerShell
• Working knowledge of Murex, MxTest, Mx pipeline and Machine Learning applications will be an advantage.

As an ML Engineer, your pivotal role involves operationalizing ML Models developed by Client data scientists. You will serve as the focal point for ML model refactoring, optimization, containerization, deployment, and quality monitoring. Your main responsibilities will include:Conduct reviews for compliance of the ML models in accordance with overall platform governance principles such as versioning, data / model lineage, code best practices and provide feedback to data scientists for potential improvements
Develop pipelines for continuous operation, feedback and monitoring of ML models leveraging best practices from the CI/CD vertical within the MLOps domain. This can include monitoring for data drift, triggering model retraining and setting up rollbacks.
Optimize AI development environments (development, testing, production) for usability, reliability and performance.
Have a strong relationship with the infrastructure and application development team in order to understand the best method of integrating the ML model into enterprise applications (e.g., transforming resulting models into APIs).
Work with data engineers to ensure data storage (data warehouses or data lakes) and data pipelines feeding these repositories and the ML feature or data stores are working as intended.
Evaluate open-source and AI/ML platforms and tools for feasibility of usage and integration from an infrastructure perspective. This also involves staying updated about the newest developments, patches and upgrades to the ML platforms in use by the data science teams.

Technical Skills

Proficiency in Python used both for ML and automation tasks
Good knowledge of Bash and Unix/Linux command-line toolkit is a must-have.
Hands on experience building CI/CD pipelines orchestration by Jenkins, GitLab CI, GitHub Actions or similar tools is a must-have.
Knowledge of OpenShift / Kubernetes is a must-have.
Good understanding of ML libraries such as Panda, NumPy, H2O, or TensorFlow.
Knowledge in the operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g., Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, Dataiku, H2O, or DKube).
Knowledge of Distributed Data Processing framework, such as Spark, or Dask.
Knowledge of Workflow Orchestrator, such as Airflow or Ctrl-M.
Knowledge of Logging and Monitoring tools, such as Splunk and Geneos.
Experience in defining the processes, standards, frameworks, prototypes and toolsets in support of AI and ML development, monitoring, testing and operationalization.
Experience in ML operationalization and orchestration (MLOps) tools, techniques and platforms. This includes scaling delivery of models, managing and governing ML Models, and managing and scaling AI platforms.
Knowledge of cloud platforms (e.g. AWS, GCP) would be an advantage.

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.

We are looking for skilled Cloud Engineers with expertise in Google Cloud Platform (GCP) to join our innovative team. The ideal candidates will have hands-on experience with IAM, Dataproc, and Vertex AI.

Key Responsibilities:

• Design, implement, and manage GCP infrastructure.
• Configure and maintain Identity and Access Management (IAM) policies.
• Deploy and optimize Dataproc clusters for big data processing.
• Utilize Vertex AI for developing and deploying machine learning models.
• Ensure security and compliance within the GCP environment.
• Collaborate with development and data science teams to meet project goals.
• Automate infrastructure deployment and management using Terraform or similar tools.
• Monitor system performance and troubleshoot issues.
• Stay current with GCP advancements and integrate best practices.

Proven experience with GCP, IAM, Dataproc, and Vertex AI.

Strong scripting and automation skills.

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 highly skilled and experienced Cloud Engineer to join our dynamic team. The Cloud Engineer will be responsible for designing, implementing, and managing scalable, secure, and reliable cloud infrastructure on GCP. The ideal candidate will have hands-on experience with IAM, Dataproc, and Vertex AI, and will be adept at optimizing cloud resources to support the company's data and AI initiatives.

Key Responsibilities:

• Design, deploy, and manage GCP infrastructure to support scalable and secure cloud solutions.
• Implement and manage IAM policies, roles, and permissions to ensure robust security and compliance.
• Develop and maintain Dataproc clusters for large-scale data processing and analytics.
• Utilize Vertex AI to build, train, and deploy machine learning models.
• Collaborate with data scientists, software engineers, and other stakeholders to optimize cloud solutions for performance and cost efficiency.
• Monitor and troubleshoot cloud infrastructure to ensure high availability and reliability.
• Stay current with GCP updates, best practices, and industry trends to continuously improve cloud solutions.
• Provide guidance and support to development teams on cloud best practices and DevOps methodologies.

• 4+ years of professional experience as Cloud Engineer
• Proven experience as a Cloud Engineer with a focus on GCP.
• Hands-on experience with IAM, Dataproc, and Vertex AI.
• Strong understanding of cloud security best practices.
• Proficiency in scripting and automation using tools such as Python, Terraform, or similar.
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.
• Excellent problem-solving skills and ability to work in a fast-paced environment.

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.

As a Power BI Engineer with visualization experience, you will be responsible for designing, developing, and maintaining business intelligence solutions using Power BI. You will work closely with various stakeholders to understand their data needs, create interactive and visually appealing dashboards, and ensure the effective use of data to drive business decisions.

• Proven experience as a Power BI Developer or in a similar role.
• Strong experience in data visualization, with a portfolio of previous Power BI projects.
• Proficiency in DAX (Data Analysis Expressions) and M (Power Query Formula Language).
• Solid understanding of data warehousing concepts and SQL.
• Excellent analytical and problem-solving skills.
• Detail-oriented with a strong focus on quality and accuracy.

Preferred Skills:

• Experience with other data visualization tools such as Tableau or Qlik.
• Knowledge of Azure Data Services, including Azure Data Factory, Azure SQL Database, and Azure Synapse Analytics.
• Understanding of data governance and data security practices.
• Familiarity with Agile methodologies and experience working in an Agile environment.

• Supporting a range of Cyber Security tools including Exabeam, CarbonBlack, Tripwire, CyberArk, TrendMicro AV, Splunk, DAM, Tenable and RSA.

• Managing designated vendors for the specified Security tools.

• Driving the scheduling of security-related projects and remediation timelines.

• Maintaining, troubleshooting, patching, and updating various security tools and scanners used in MAS.

• Recommending process re-engineering and streamlining to enhance workflows and efficiencies.

• Delivering management reporting and dashboarding to stakeholders, including data and trend analysis, and recommending next steps.

• Following up on remediation actions, security and risk assessments with respective stakeholders and applications teams.

• Conducting daily health check and validating system availability through various monitoring/checks.

• Implementing of the service requests, change requests and support of incident management.

• Fine tuning of rules, updating of contents packs to suit the different use cases in

• Experience in Market Risk, leading a high-performance team and large-scale high-impact projects on Market Risk, Counterparty Credit Risk, Risk Analytics for risk analysis, monitoring, and reporting.
• Building financial models, pricing derivatives, automating reports, and building trusting relationships with stakeholders including Traders, Risk, IT, Compliance & Audit
• Solid knowledge of Capital Markets products (e.g., Fixed Income, FX, Derivatives, Futures, Swaps), Market Risk methodologies and regulations (e.g., Value-at-Risk, Stress Testing, Back Testing, Basel II, FRTB)
• Proficient at Excel Macro, SQL, Python, MATLAB, STATA, Tableau, Bloomberg, Capital IQ, PowerPoint, Unix Bash
• Monitored daily market risk for Global Fixed Incomes Credit, Equity Derivatives and Prime Services; enhanced daily market risk reports and regulatory reports by using Excel, VBA, Tableau and Python
• Managed the projects by collaborating with IT and Data team and enhanced operation process by conducting reconciliations and automating procedures using Python & Unix Bash script to deliver timely risk reporting.
• Prepared FRTB Quantitative Impact Study (QIS) reports and presentations for Executives and chaired meetings by understanding expectations, creating project plans, and making recommendations for potential issues.
• Mentored and coached junior staff and held career development sessions to inspire/motivate high performances.