Total 19 data entry clerk job vacancies in Singapore

• Perform operation, installation, and monitoring of big data platforms
• Ensure the reliability and normal operation of multiple core systems for big data and online computing, resolving issues within the agreed SLA
• Evaluate infrastructure requirements for deployments and upgrade activities
• Develop and maintain technical documentations related to design, configuration, troubleshooting, backup, DR, etc
• Ensures deployment and operations of the data platform comply with prevailing security, regulations and audit requirements
• Provide recommendations on data governance practices and in-depth optimizations best practices

Requirements:
primary skillset: DevOps and system engineers in Unix
• Solid computer software basic knowledge; understand Linux operating system, storage, network IO and other related principles
• Familiar with one or more programming languages, such as Python/Go/Java/Shell/Ansible
• Experience with Cloudera, Informatica, or Denodo and its runtime components would be highly advantageous
• Relevant computing/distributed/big data system experience (Hadoop/HDFS /Kubernetes/Docker/OpenStack/Hadoop/Spark/Flink,etc.) would be advantageous
• Good data structure and system design skills highly preferred
• Good knowledge of information security highly

EA License No: 11C4879 / Registration ID : R1218583

Apar Technologies Pte Ltd, Singapore

About the role:

This role will be supporting data engineering activities for the Enterprise Data Warehouse in major project initiatives for Data Strategy Group

Your background:

• • Possess a degree in Computer Science/Information Technology or related field.
• Strong hands-on experience in Oracle PL/SQLand Informatica PowerCenter.
• Strong hands-on SQL skill in any RDBMS.
• Experience in the Systems Development Life Cycle (SDLC) implementation methodology and/or Agile methodologies such as Scrum and Kanban.
• Agile, fast learner, and able to adapt to changes.
• Good team player, with strong analytical skill and enjoy complex problem-solving.

EA License: R1873481

Company EA License: 11C4879

Job Description

• Desired Candidate Profile Technology Engineering Expertise
• 5 years of experience in implementing data solutions using GCPSQL programming
• Proficient in dealing data access layer RDBMS NOSQL
• Experience in implementing and deploying Big data applications with AWSGCP Big Data Services
• Must have excellent SQL skills
• Experience with different development methodologies RUP Scrum XP Soft skills Able to deal with diverse set of stakeholders
• Proficient in articulation communication and presentation
• High integrity
• Problem solving skills learning attitude
• Team player Key Responsibilities
• Implement data solutions using AWSGCP and need to be familiar in programming with Java
• Ensure clarity on NFR and implement these requirements
• Work with Client Technical Manager by understanding customer’s landscape

EA Number: 11C4879

About the Role:
We are seeking an experienced Senior Data Solutions Engineer with a strong focus on Google Cloud Platform (GCP) to design, implement, and deploy cutting-edge data solutions. You will collaborate with diverse stakeholders, ensuring clarity of requirements and delivering high-quality solutions aligned with business objectives.

Key Responsibilities:

• Design and implement data solutions exclusively on GCP.
• Develop and maintain efficient data access layers using RDBMS and NoSQL technologies.
• Build and deploy Big Data applications leveraging GCP Big Data Services.
• Collaborate with the Client Technical Manager to understand customer requirements and their technical landscape.
• Ensure clarity and implementation of non-functional requirements (NFRs).
• Utilize programming skills in Java to develop robust solutions.

Desired Candidate Profile:

• 5+ years of experience implementing data solutions using GCP and SQL programming.
• Expertise in SQL and proficiency with RDBMS and NoSQL databases.
• Solid experience with development methodologies such as RUP, Scrum, and XP.
• Exceptional communication, articulation, and presentation skills.
• Strong problem-solving skills, a learning mindset, and high integrity.
• A collaborative team player capable of engaging with diverse stakeholders effectively.

EA License: R1873481

Company EA License: 11C4879

Data Project Manager

Key Requirements:

• Bachelor’s degree in Computer Science, Information Technology, or a related field (Master’s degree preferred).
• 5+ years of experience managing data-driven projects with a strong understanding of data technologies.
• Proven experience with big data platforms and technologies such as Hadoop and Kafka.
• Strong experience in managing cross-functional teams across multiple geographies and time zones.
• Solid understanding of Agile project management methodologies (e.g., Scrum, Kanban).
• Excellent communication, leadership, and interpersonal skills.
• Ability to balance competing priorities, manage risks, and meet deadlines in a fast-paced environment.
• Experience with data governance, security, and compliance processes.
• Strong problem-solving skills and ability to think critically and strategically.

Desirable Skills:

• Certification in Project Management (e.g., PMP, Scrum Master) or similar certifications.
• Familiarity with additional data technologies such as Spark, Flink, and SQL-based analytics.
• Experience with cloud platforms (AWS, Azure, Google Cloud).

EA License No: 11C4879 / Registration ID : R1218583

Apar Technologies Pte Ltd, Singapore

Key Responsibilities:

• Collaborate with business stakeholders to gather, understand, and translate data requirements into actionable solutions.
• Implement scalable and reusable data processes to meet evolving business needs.
• Work closely with engineering teams and external data vendors to troubleshoot and resolve technical data-related issues.
• Provide timely support to end users, addressing data queries and issues.
• Develop and maintain comprehensive documentation for data management activities, including operating models, processes, and test results.
• Monitor the effectiveness of data initiatives and recommend continuous improvements.
• Stay updated on the latest industry trends and best practices in data management.

Mandatory Skills:

• A degree in Computer Science, Information Technology, or related fields.
• Proven experience in data management areas such as metadata, data quality, and data discovery.
• Strong understanding of financial data and data management best practices.
• Demonstrated knowledge of data security and technical challenges faced by large organizations.
• Extensive hands-on experience with SQL and relational databases such as Snowflake, Microsoft SQL Server, and Oracle.
• Familiarity with data management trends and practices in the financial industry.
• Excellent analytical, communication, problem-solving, and documentation skills.
• Ability to work both independently and collaboratively as part of a team.

Preferred Skills:

• Experience with Python programming.
• Certification in data management or data quality (e.g., DAMA, CDMP).

EA License: R1873481

Company EA License: 11C4879

About the Role:
We are seeking a highly motivated Metadata Specialist to join our team. In this role, you will play a key part in the implementation and management of metadata to support enterprise data governance and compliance initiatives. If you have a strong background in data management, problem-solving, and stakeholder engagement within the financial services domain, we’d love to hear from you.

Key Responsibilities:

• Manage metadata activities across the entire lifecycle, including collection, quality control, and maintenance.
• Conduct thorough reviews of metadata to ensure accuracy, quality, and compliance with organizational governance standards.
• Provide recommendations on metadata improvements based on stakeholder input and governance guidelines.
• Support the onboarding of stakeholders, particularly within financial institutions, into the organization's data governance and compliance roadmaps.
• Collaborate with cross-functional teams to ensure metadata aligns with enterprise data management objectives.
• Identify, analyze, and resolve metadata challenges to support effective data discovery and utilization.

Required Skills and Qualifications:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Proven experience with metadata management, quality control, and governance processes.
• Strong problem-solving skills, with the ability to analyze complex metadata issues and provide actionable solutions.
• Experience in stakeholder engagement, particularly in guiding financial institutions through data governance frameworks.
• Excellent communication and interpersonal skills to collaborate with various teams and stakeholders.

Preferred Qualifications:

• Familiarity with enterprise data governance tools and platforms.
• Experience in metadata management within financial institutions or highly regulated industries.
• Knowledge of compliance and data governance best practices.

EA License: R1873481

Company EA License: 11C4879

Job Description

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Proven experience as a Big Data Engineer or similar role.
• Strong proficiency in Apache Spark and Scala programming.
• Experience with big data technologies such as Hadoop, Hive, Kafka, etc.
• Familiarity with data warehousing concepts and tools.
• Knowledge of SQL and NoSQL databases.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Experience with cloud platforms like AWS, Azure, or Google Cloud.
• Knowledge of machine learning frameworks and libraries.
• Experience with containerization and orchestration tools like Docker and Kubernetes.

EA Number: 11C4879

We are seeking a skilled and motivated Data Engineer

With expertise in Scala, SQL, and Hadoop, to join our dynamic team. In this role, you will design, develop, and maintain scalable data pipelines and systems to process large datasets. You will collaborate with cross-functional teams to deliver high-quality solutions for data storage, transformation, and analytics.

Key Responsibilities

1. Data Pipeline Development

• Design, build, and optimize scalable data pipelines using Scala and Hadoop frameworks.
• Implement ETL processes for ingesting, transforming, and storing data from various sources.

2. Data Analysis and Query Optimization

• Write and optimize complex SQL queries for efficient data retrieval and transformation.
• Troubleshoot and resolve performance issues in queries and data workflows.

3. Big Data Ecosystem Management

• Manage Hadoop-based data infrastructure, including HDFS, Hive, and related components.
• Monitor system performance and optimize resource utilization in a distributed environment.

4. Collaboration and Problem-Solving

• Work closely with data analysts, data scientists, and business stakeholders to understand requirements and translate them into technical solutions.
• Provide technical guidance and best practices for data engineering within the team.

5. Automation and Monitoring

• Develop scripts and tools to automate repetitive tasks and enhance system monitoring.
• Ensure data quality and consistency through validation and monitoring mechanisms.

6. Documentation and Compliance

• Document technical solutions, workflows, and processes to ensure knowledge sharing and reproducibility.
• Ensure compliance with data governance and security policies.

Requirement/Skillsets:

Technical Skills:

• Proficiency in Scala programming and functional programming principles.
• Strong SQL skills, including query optimization and database design.
• Hands-on experience with Hadoop ecosystem tools (HDFS, Hive, YARN, MapReduce).
• Familiarity with other big data tools like Spark, Kafka, or Flink is a plus.

Problem-Solving:

• Strong analytical skills with the ability to troubleshoot and resolve complex data issues.

Communication:

• Excellent communication skills to effectively collaborate with technical and non-technical stakeholders.

Experience:

• 6+ years of experience in data engineering, big data technologies, or a similar role

EA License: R1873481

Company EA License: 11C4879

Job Description

Role: Senior ETL Test Lead

Must Have:

• At least 10+ yrs. quality assurance with exposure/experience in Agile Development environments for DWH/ETL Projects.

• Experience with Query Surge automated testing tools or equivalent automation skills.

• Can write ETL Testing scripts (using SQL/Python)

• Have deep knowledge of Data Warehousing concepts, ETL Process and cloud systems.

• Has strong testing experience with snowflake and on prem Hadoop and Teradata

• Hands on experience of different DBs like, MS SQL Server, Oracle, DB2 etc.

• 2-3 yrs. Of Domain Knowledge for Banking Projects.

• Identifies, communicates, and escalates issues as required

• A team player and self-starter who will work side by side with the development team

• Ability to multi-task, prioritize tasks and quickly adjust in a rapidly changing environment

• Excellent verbal and written communication skills

• Thorough working knowledge of software testing methodologies and the testing life cycle

Good to have:

• Data Migration testing projects for Cloud or on- premise databases.

• Ability to work independently with clients, proactive, and self-managed

• Solicitation and elicitation of client needs and requirements

• Project Management and Software Development Methodologies

• Industry experience in Banking domain is beneficial

• Familiarity/exposure to programming languages and SQL to allow for defect triaging and automation

• Familiarity/exposure to scripting languages used in test automation

EA Number: 11C4879

About the Role

We are seeking a highly skilled and detail-oriented Data Management Specialist to join our dynamic team. This role is ideal for individuals with a strong background in data management, analytics, and engineering, particularly within the investment and banking industries. You will work closely with diverse stakeholders to design, implement, and maintain robust data lifecycle solutions.

Key Responsibilities

• Collaborate with business users (e.g., research analysts, quantitative strategists) and technical teams (e.g., data engineers, data scientists) to develop and support data lifecycle solutions such as data onboarding and distribution.
• Validate and contribute to the design of lifecycle data solutions to ensure alignment with business and operational needs.
• Oversee day-to-day operations, including metadata collation, analysis of system operations data (e.g., data quality metrics), and data distribution service usage.
• Perform data access control operations, ensuring compliance with enterprise data governance and handling standards.
• Serve as the Center of Excellence for common data lifecycle services by defining standards, best practices, and workflow processes to improve operations and ensure compliance.
• Monitor, analyze, investigate, and resolve operational incidents while providing advisory support to users.
• Continuously identify opportunities for improvement in processes and operations.
• Build and maintain strong stakeholder relationships to support current and future data lifecycle needs.

Mandatory Skills and Qualifications

• Education: Degree in Accounting, Finance, Engineering, Computer Science, Information Technology, or a related field from a recognized tertiary institution.
• Experience: Minimum 5 years in data management, analytics, or engineering, preferably within the investment or banking industries.
• Technical Expertise:Strong knowledge of data management principles, key controls, and processes, including data integration and distribution.
  Proficiency in programming languages such as Python, Java, and SQL.
  Familiarity with data visualization tools (e.g., Tableau, Power BI) and virtualization technologies (e.g., Denodo) is a plus.
  

Skills:

• Meticulous and detail-oriented with a strong focus on operational accuracy.
• Proven ability to design and implement solutions and conduct code reviews.
• Excellent written and verbal communication skills.
• Strong interpersonal skills to interact effectively with diverse stakeholders.
• Agile and quick to learn, with the ability to adapt to changing environments.
• Strong analytical skills and a passion for solving complex problems.
• Experience with SDLC implementation methodologies and/or Agile frameworks like Scrum and Kanban.

EA License: R1873481

Company EA License: 11C4879

Responsiblities:

• Perform data extraction, cleaning, transformation, and flow. Web scraping may be also a part of the work scope in data extraction.
• Design, build, launch and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks
• Collaborate with Project Manager, Visualisation Developer, Data Scientist, UX Designers and Data Analyst to build scalable data-driven products
• Work in an Agile Environment that practices Continuous Integration and Delivery
• Support and advise best practices in data management standards, policies and procedures
• Work closely with fellow developers through pair programming and code review process
• Integrate and collate data silos in a manner which is both scalable and compliant
• Be responsible for developing backend APIs working on databases to support the applications

Requirement/Skillset:

• To take up BAU Ops tasks for existing on-premise data warehouse
• Talend
• Tableau
• MS SQL
• Fresh graduates with good degree or mid-career conversion is welcome

EA License Number : 11C4879

Job Description

The candidate should possess the following: At least (2) years of hands-on experience as Azure Data Engineer using:

Azure Data Factory Azure Synapse Analytics / Datawarehouse

Preferably with relevant certifications from Microsoft including Azure Data Engineer Associate

At least (3) years of hands-on experience in

- Performing data Ingestion using Data factory T-SQL stored procedure and data harmonizing

- Implementing Data Quality validation

- At least (3) years of hands-on experience in

- Providing technical support (80%) enhancements (20%) for existing applications in Azure

(Team has several ongoing projects on the Azure platform, including Finance, Commercials, and Operations. This role requires a support engineer primarily focused on existing projects and understanding the teams dynamics. The role requires someone capable of directly addressing system issues and resolving them. Users report issues, such as error messages and screenshots etc. The data engineer needs to log into the production system, trace processes end-to-end, identify the root cause, and resolve the problem. The engineer is expected to verify the accuracy of data and processes, ensuring correct numbers and outputs.)

Good to have following skills

Knowledge of Azure Databricks

Data modelling in Azure Analysis Services using star and snowflake schema.

Knowledge of writing DAX query to create measures dimensions.

Python Coding Experience

Non-Technical Skills Requirements (Business Skills) At least (3) years of relevant experience in:

Business Requirement Analysis.

EA Number: 11C4879

Key Responsibilities

Business Understanding

• Conduct thorough business requirement analysis to bridge the gap between business needs and technical solutions.
• Understand business processes and systems to support various functions such as Finance, Commercials, and Operations.
• Serve as a liaison between business and technical users, ensuring effective communication and understanding.

Azure Data Engineering

• Develop and maintain data pipelines using Azure Data Factory.
• Utilize Azure Synapse Analytics/Datawarehouse for data processing and analysis.
• Collaborate on projects leveraging Microsoft Azure Data Engineer Associate certifications (preferred).

Data Ingestion & Modeling

• Perform data ingestion tasks using Data Factory, T-SQL stored procedures, and data harmonization techniques.
• Implement and validate data quality checks to ensure accurate outputs.
• Design data models in Azure Analysis Services using star and snowflake schemas.
• Create dimensions and measures using DAX queries.
• Utilize Python for advanced data transformations and processing (preferred).

Technical Support

• Provide technical support (80%) and enhancements (20%) for existing Azure applications.
• Address system issues by identifying root causes and resolving them in a timely manner.
• Trace processes end-to-end to verify data accuracy and ensure seamless operations.
• Maintain documentation and logs for issue resolution and enhancements.

Others

• Utilize Microsoft Office products effectively to document processes and communicate updates.
• Stay updated on the latest tools and techniques in Azure data engineering.

Qualifications

• 3+ years of experience in Business Requirement Analysis and Process/System Understanding.
• 2+ years of hands-on experience as an Azure Data Engineer using Azure Data Factory and Azure Synapse Analytics/Datawarehouse.
• Strong knowledge of data modeling and data validation techniques.
• Technical proficiency in DAX, Python, and Azure Databricks (preferred).
• Familiarity with providing technical support and resolving issues in Azure-based production systems.
• Relevant Microsoft certifications, such as Azure Data Engineer Associate, are an advantage.

EA License Number: 11C4879

The successful candidate will play a pivotal role in designing and implementing solutions for automating data services processes. This position requires strong technical expertise, analytical problem-solving skills, and effective collaboration within a team-oriented environment.

Key Responsibilities:

• Develop, deploy, and maintain automation solutions for data services.
• Write efficient and maintainable code using Python, SQL, and PL/SQL.
• Leverage CI/CD pipelines to enhance deployment and automation processes.
• Work with data warehouses such as Snowflake and Oracle to optimize data workflows.
• Collaborate with cross-functional teams to analyze requirements and deliver effective solutions.
• Troubleshoot and resolve issues in automation systems and data pipelines.
• Contribute to the continuous improvement of existing processes and technologies.

Mandatory Skills and Qualifications:

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Proficient in Python, SQL, and PL/SQL.
• Experience with CI/CD pipelines for automation and deployment.
• Familiarity with data warehouses like Snowflake and Oracle.
• Strong analytical and problem-solving abilities.
• Excellent communication and teamwork skills.

Preferred Qualifications:

• Experience in data engineering or data services roles.
• Familiarity with cloud platforms and big data technologies.

EA License Number : 11C4879

Responsibilities:

• Design and build scalable data pipelines using AWS services such as Glue, Redshift, S3, and EMR to process and transform large datasets.
• Implement best practices for data storage, data lakes, and data warehousing on AWS to ensure optimal performance, security, and cost-efficiency.
• Develop and integrate Generative AI models using AWS SageMaker, Bedrock, and other AI/ML services to deliver intelligent automation and insights.
  Build, train, and fine-tune machine learning models, including Generative AI models, for various business use cases.
• Implement data governance frameworks to ensure data integrity, quality, and compliance with industry regulations.
• Secure data environments by enforcing best practices for AWS Identity and Access Management (IAM), encryption, and data privacy policies.
• Automate data processing and machine learning workflows using AWS Lambda, Step Functions, and Infrastructure-as-Code (IaC) tools like CloudFormation or Terraform.
• Continuously optimize data architectures and AI solutions to reduce costs and improve performance.
• Collaborate with cross-functional teams to identify business challenges and design data-driven AI solutions that address them.
• Provide technical guidance to teams on AWS data services and AI/ML best practices.
• Monitor and maintain the performance of data pipelines, AI models, and AWS infrastructure, ensuring they are robust, reliable, and scalable.
• Troubleshoot data and AI model issues, providing timely resolutions to maintain uninterrupted operations.

Your skillsets/requirement:

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related fields.
• 3-5 years of hands-on experience in AWS data engineering and AI/ML projects.
• Proven experience with AWS services such as Glue, Redshift, S3, SageMaker, and Lambda

Job Description

We are seeking an experienced Senior Data Architect with extensive expertise in Snowflake Data Warehouse and data engineering to join our team. This role requires an individual with a deep understanding of data architecture principles, a strong foundation in data warehousing and ETL processes, and hands-on experience in building large-scale data solutions. The ideal candidate should have experience with data pipelines, orchestration, data quality, and governance, along with a robust technical background in Snowflake, Python, and streaming services.

Responsibilities

• Architect and Implement Snowflake Solutions: Design and oversee the implementation of large-scale data intelligence solutions leveraging Snowflake DW.
• Data Pipeline and Platform Development: Build, optimize, and manage data pipelines, orchestration tools, and data governance frameworks to ensure efficient data flows and high-quality data output.
• Strategic Data Analysis: Perform data quality checks, enforce data governance standards, and apply data quality rules to maintain data integrity.
• Data Engineering & Streaming Services: Utilize expertise in Python or Scala, and work with streaming services such as Kafka to support real-time data processing and analytics.
• Work with Semi-Structured Data: Effectively handle semi-structured data formats, ensuring seamless integration with the Snowflake platform.
• SQL Proficiency: Develop complex SQL queries and leverage SQL proficiency for advanced data manipulation, analysis, and integration tasks.
• Architectural Design: Lead architecture and design efforts for Snowflake DW, establishing best practices for scalable, high-performance data environments.

Qualifications

• Experience: 10+ years in IT, with a strong focus on data architecture and engineering.
• Snowflake Expertise: In-depth knowledge of Snowflake architecture, functions, and data warehousing concepts.
• ETL and Data Modeling: Advanced understanding of ETL processes, data warehousing, and data modeling structures.
• Programming Skills: Proficiency in Python or Scala, with experience in data processing and engineering tasks.
• Streaming Services: Solid experience with Kafka or similar streaming services.
• Data Governance and Quality: Proven ability to establish and maintain data quality standards, governance policies, and best practices for data integrity.
• Communication and Design: Strong analytical and architectural design skills, with the ability to clearly communicate complex technical concepts to diverse stakeholders.

This role is perfect for a highly skilled data architect who excels in designing and implementing robust Snowflake-based solutions and is passionate about leveraging cutting-edge data technologies.

EA License Number : 11C4879

About the role and your skillset:

• Possess a degree in Computer Science/Information Technology or related fields.
• Experience in data analysis.
• Experience in managing data reconciliation/quality checks (implementation, monitoring and troubleshooting).
• Able to handle data issue management.
• Proficient in Oracle PL/SQL.
• Experience in performing UAT.
• Able to manage SLA and queries from end users.
• Provide documentation support in technical/functional specifications.
• Possess investment data domain knowledge.
• Good problem solving and logical thinking.

EA License Number : 11C4879

Responsibilities:

1. Setup and Configure Reporting Platform: Collaborate with business stakeholders to understand and translate business and functional requirements into precise technical specifications.
   Develop, implement, and manage Extract, Transform, Load (ETL) scripts for data integration and migration tasks.
   Create complex queries and develop comprehensive reports to present data insights effectively.
   Conduct unit testing, troubleshoot, and resolve any defects to ensure seamless reporting and data integration.
   

Skills and Experience Requirements:

Must-Have:

1. Azure Data Factory (ADF): At least 2-3 years of experience with ADF, including developing pipelines to migrate and transform data.
   Skilled in creating complex ADF jobs involving the transformation of multiple tables.
   Familiarity with ADF terminologies and coding standards to ensure best practices are followed.
   
2. Azure Synapse: Solid understanding of Azure Synapse databases, including data distribution, indexing, and record processing.
   Experience configuring Synapse databases for concurrent processing of large datasets and integrating with ADF pipelines.
   Knowledge of access control setups, including the use of service accounts for secure database access.
   
3. Power BI SaaS: Minimum of 2-3 years of experience with Power BI, including the use of Power BI Desktop and builder tools to develop and enhance paginated reports.
   Proficiency in creating complex, interactive dashboards that provide valuable business insights.
   In-depth understanding of Power BI licensing models (Free, Pro, Premium) and workspace access management.
   Experience setting up and configuring Power BI Gateways for secure and reliable data connections.
   

Good to Have:

• Strong problem-solving skills and the ability to optimize data processes for performance and efficiency.
• Experience with cloud platforms and data integration tools.
• Understanding of data warehousing concepts and database management systems.
• Ability to communicate effectively with cross-functional teams and present technical concepts to non-technical stakeholders.

This position requires a self-starter who can adapt to changing requirements and work independently or as part of a team to deliver high-quality data solutions.

EA License Number : 11C4879