1,761 Data Developer jobs in Singapore

Job Overview

• We are seeking a highly skilled Data Engineer to join our team. In this role, you will be responsible for designing, developing, and maintaining scalable data pipelines and systems that handle large datasets.

Key Responsibilities:

• Design, build, and optimize scalable data pipelines using functional programming concepts and frameworks like Scala.
• Implement Extract, Transform, Load (ETL) processes to ingest, transform, and store data from various sources.
• Write and optimize complex Structured Query Language (SQL) queries for efficient data retrieval and transformation.
• Troubleshoot and resolve performance issues in queries and data workflows.
• Manage and maintain distributed data infrastructure, including Hadoop-based components like HDFS, Hive, and YARN.
• Monitor system performance and optimize resource utilization in a distributed environment.
• Collaborate closely with data analysts, data scientists, and business stakeholders to understand requirements and translate them into technical solutions.
• Provide technical guidance and promote best practices for data engineering within the team.
• Develop scripts and tools to automate repetitive tasks and improve system monitoring.
• Ensure data quality and consistency through validation and monitoring mechanisms.
• Document technical solutions, workflows, and processes to enable knowledge sharing and reproducibility.
• Ensure adherence to data governance and security policies.

• Design and develop data warehouses and big data systems.
• Develop and maintain ETL processes using Apache Spark, Scala, and Python.
• Implement data pipelines using Hadoop, Kafka, and Docker.
• Ensure data quality and integrity through regular testing and validation.
• Maintain expertise in AWS cloud architecture and services, including Terraform for cloud deployment.

• Bachelor's degree in Computer Science or related field.
• 8-12 years of experience in data warehousing and big data technologies.
• Extensive knowledge of ERD design, ETL, querying, and data management.
• Minimum 6-8 years of Python development experience in data engineering.
• Minimum 8-10 years of SQL experience.
• Experience with CI/CD, Kubernetes, and containerization using Docker.

• Opportunity to work with cutting-edge technology.
• Collaborative and dynamic work environment.
• Professional growth and development opportunities.

We are a leading organization in the tech industry, dedicated to innovation and excellence.

We are seeking a seasoned data engineer to lead the design and development of high-volume, multi-terabyte 24/7 data warehouses.

Key Responsibilities:

• Create scalable data integration solutions using Abinitio and Python with PySpark.
• Build robust and fast ETL applications adhering to modern best practices.
• Collaborate with cross-functional teams to deliver high-performance data integration projects.

Technical Requirements:

• Proven experience with Abinitio development tools (GDE, EME, Conduct).
• Strong programming skills in Python and PySpark for large-scale data processing.
• Develop logical and physical data models; experience with Fastload, Multiload, TPT, T-Pump.
• SQL development expertise (Oracle PL/SQL preferred).

Skills & Qualifications:

• Excellent understanding of data architecture and data engineering principles.
• Experience with data warehousing and business intelligence systems.
• Ability to work effectively in a team environment.

We are seeking a skilled professional to join our corporate lab. The successful candidate will be primarily involved in data analytics and machine learning.

The role involves working on modeling analytical data collected from various sources using ML or AI for food product development.

• Manage and preprocess large datasets
• Code and script based on specified tasks using languages such as R, Python, Java, and Bash
• Apply statistical analysis and machine learning experience in areas including optimization algorithms, supervised and unsupervised learning, sampling algorithms, and deep learning algorithms
• Summarize results for reporting purposes
• Participate in seminars and research-in-progress meetings within the team and collaborators

A PhD in Statistics, Data Science, or Computer Science is required.

• A team player with ability to communicate technical concepts to non-technical stakeholders
• Ability to learn new computational techniques and apply them to solve open problems

We are seeking a talented Software Developer with expertise in data analysis and processing to join our team.

The ideal candidate will have experience working with Java/JEE technologies in Unix environment, as well as knowledge of Spark, Hadoop, and Big Data technologies.

Key skills and qualifications include:

• Minimum 4 years' experience in web and stand-alone application design & development with Java/JEE technologies in Unix environment.
• Must have knowledge on Spark, Hadoop to analyze and transform large amount of data.
• Must have knowledge on HBase, Janus graph, gremlin, elastic search to perform CRUD operations on big data.
• Should have knowledge on maven, gradle, Jenkins, UML build tools to manage and build project.
• Should have knowledge on GIT, GIT Lab, Junit, Cucumber, Jira, Sonar to manage/test source code effectively.
• Should have good knowledge on Spring, Spring REST, Web services, gRPC, Micro services, ORM framework to implement robust API's.
• Must have knowledge on Kibana, spark UI, ELK to debug and identify the root cause of the issues.

A strong understanding of application system design, development, testing, deployment and maintenance is also required. Additionally, good knowledge of different design patterns and working experience with Agile Methodology in at least one project are necessary.

We value professionals who can tell employers about their relevant skills.

Key Skills:
Git
Spring
Big Data
Hadoop
Unix
JUnit
Spark
JIRA
Kibana
Java
J2EE

We are seeking a skilled professional to fill a Senior Software Engineer position.

This role will involve designing and developing SQL Server stored procedures, functions, views, and triggers for the ETL process. Additionally, the successful candidate will design and develop SSRS / SSIS / SQL ETL solutions to acquire and prepare data from numerous upstream systems.

• Design and development of database objects (tables, views, indexes)
• Experience working with SSIS, SSRS packages
• Proficient with ETL tools such as Microsoft SSIS, SSRS
• Strong understanding of Agile methodology
• JavaScript expertise

1. Build data transformations with SSIS including importing data from files, moving data from one database platform to another.
2. Debug and tune SSIS, SSRS or other ETL processes to ensure accurate and efficient movement of data.
3. Analyze and develop strategies and approaches to import and transfer data between source, staging, and ODS/Data Warehouse destinations.
4. Test and prepare ETL processes for deployment to production and non-production environments.
5. Support system and acceptance testing including the development or refinement of test plans.

A dynamic company that values innovation and excellence is looking for talented individuals who share our passion for software engineering and are eager to take on new challenges.

Position Summary:

We are seeking a highly experienced and strategic Senior Data Analyst/Developer with over 12+ years of progressive experience, possessing a robust background in data analysis, business intelligence, and a deep understanding of data warehousing concepts, including PL/SQL, ETL processes, IBM DataStage, and Enterprise Application Integration (EAP). The ideal candidate will be a critical thinker with exceptional analytical skills, capable of translating complex data into actionable insights for business stakeholders. The successful candidate will be instrumental in Data Analysis for Genesis Application which delivers Regulatory & Consent Order items for Regulatory & Fed Reports. This role requires not only strong technical acumen but also significant experience in leading data initiatives, mentoring junior analysts, and influencing data strategy.

Key Responsibilities

• Advanced Data Analysis & Insight Generation: Lead complex data analysis initiatives to identify trends, patterns, and anomalies in large datasets. Develop sophisticated reports, dashboards, and analytical models to provide actionable insights that drive business decisions across various departments.
• Requirements Gathering & Solution Design: Collaborate extensively with business stakeholders (e.g., product managers, marketing, finance, operations) to deeply understand their analytical needs and business questions. Translate these into detailed data requirements and propose optimal analytical solutions.
• Data Sourcing & Transformation: Work closely with Data Engineers and ETL developers to identify, source, and ensure the availability and quality of necessary data. Utilize strong understanding of PL/SQL to query complex relational databases and validate data accuracy.
• ETL Process Understanding & Validation: Leverage deep knowledge of ETL processes, particularly with IBM DataStage, to understand data lineage, transformations, and potential impacts on data analysis. Proactively identify data quality issues within ETL pipelines and work with engineering teams for resolution.
• Enterprise Application Integration (EAP) Context: Understand how data flows through various enterprise applications via EAP layers. This knowledge will be crucial for comprehending data availability, latency, and consistency for accurate analysis.
• Data Modeling & Architecture Awareness: Possess a solid understanding of data warehousing concepts, dimensional modeling, and database schemas. Provide input and feedback on data model designs from an analytical consumption perspective.
• Reporting & Dashboarding: Design, develop, and maintain advanced business intelligence solutions, including interactive dashboards and automated reports, using industry-leading BI tools.
• Mentorship & Guidance: Provide technical guidance, mentorship, and support to junior data analysts. Share best practices in data extraction, analysis, visualization, and communication.
• Data Governance & Quality: Champion data quality and integrity. Develop and implement data validation rules and processes to ensure the reliability and accuracy of analytical outputs. Adhere to organizational data governance policies.
• Performance Optimization (Analytical): Optimize complex SQL queries and data extraction processes to ensure efficient data retrieval for analysis and reporting.
• Communication & Presentation: Clearly and effectively communicate complex analytical findings, insights, and recommendations to both technical and non-technical audiences through compelling presentations and written reports.
• Strategic Contribution: Contribute to the overall data strategy, helping to define key metrics, identify data gaps, and recommend data infrastructure improvements.

Required Qualifications

• Experience: Minimum of 15 years of progressive experience in a Data Analyst, Business Intelligence Analyst, or similar role, with a strong focus on enterprise-level data.
• PL/SQL Expertise: Advanced proficiency in writing complex SQL queries and PL/SQL scripts for data extraction, manipulation, and analysis from large relational databases (preferably Oracle).
• ETL & Data Warehousing Knowledge: In-depth understanding of ETL processes, data warehousing principles, dimensional modeling (star schema, snowflake schema), and concepts like Slowly Changing Dimensions (SCDs).
• DataStage Familiarity: Solid understanding of IBM DataStage or similar enterprise-grade ETL tools, including the ability to understand job flows, source-to-target mappings, and data transformations. While not a developer role, the ability to comprehend complex DataStage implementations is crucial.
• EAP Awareness: A good understanding of Enterprise Application Integration (EAP) concepts and how data moves across different business systems via integration layers (e.g., APIs, message queues).
• BI Tool Proficiency: Expert-level experience with at least one leading Business Intelligence/Visualization tool (e.g., Tableau, Power BI, Qlik Sense, Cognos).
• Analytical Skills: Exceptional analytical, quantitative, and problem-solving skills with a proven ability to interpret data, analyze results, and provide data-driven recommendations.
• Communication: Excellent verbal and written communication skills, with a proven ability to present complex analytical findings clearly and concisely to diverse audiences.
• Data Governance & Quality: Strong commitment to data quality, accuracy, and governance.
• Mentorship: Demonstrated experience in mentoring and guiding less experienced team members.

Preferred Qualifications

• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Economics, or Business Administration.
• Experience with statistical analysis tools (e.g., R, Python with Pandas for advanced analytics.
• Familiarity with cloud-based data platforms (e.g., AWS Redshift, Azure Synapse, Google BigQuery).
• Experience with big data technologies (e.g., Hadoop, Spark).
• Domain expertise in a specific industry (e.g., Finance, Banking).

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Job Description

Data Ingestion Engineer Role Summary:

We are seeking a skilled and experienced Data Ingestion Engineer to spearhead the development and optimization of machine learning models and algorithms in our organization.

Key Responsibilities

• Design, develop, and optimize machine learning models and algorithms to drive business growth and improve operational efficiency.
• Collaborate with cross-functional teams to gather requirements, deploy models effectively, and ensure seamless integration with existing systems.
• Train and fine-tune ML models using appropriate algorithms and tools to enhance model performance and accuracy.
• Evaluate model performance using methods such as cross-validation and hyperparameter tuning to inform data-driven decision making.
• Deploy models in production environments and monitor their performance to identify areas for improvement.
• Routine maintenance of deployed models, refinement based on user feedback and performance metrics to ensure continuous quality improvement.
• Perform exploratory data analysis to uncover trends and insights that drive business strategy and inform product development.

Required Skills and Qualifications

• Bachelor's Degree in Computer Science, Data Science, Statistics, or a related field.
• At least 4 years of experience in designing, developing, and deploying ML models with a proven track record of success.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn with expertise in algorithmic design and optimization.
• Strong understanding of statistical analysis and probability theory with the ability to apply theoretical concepts to practical problems.

Benefits

The ideal candidate will have the opportunity to work with a talented team of professionals who share a passion for innovation and collaboration. This role offers a competitive salary, comprehensive benefits package, and opportunities for professional growth and development.

Others

This is an exciting opportunity for a seasoned Data Ingestion Engineer to join our team and contribute to driving business success through data-driven decision making and innovative solutions.