Design and implement scalable data architecture using AWS services such as S3, Glue, Redshift, Lambda, and Step Functions.
Build and maintain robust ETL/ELT pipelines to transform raw data into clean, structured datasets.
Ensure data solutions are reliable, high-performing, and production-ready.
Ensure strong data governance, security, and quality control across all pipelines and datasets.
Write clean, well-documented code and support testing, automation, and version control practices.
Collaborate closely with analysts, business stakeholders, and IT teams to understand data needs and deliver user-friendly data solutions.
Contribute to a knowledge-sharing culture and help uplift the technical standard of the team.

Requirements :

Minimum 4-5 years of experience in data engineering, with at least 2 years working in cloud-based environments (preferably AWS).
Experience in building and managing data models and data pipelines for large-scale data environments.
Proficiency in AWS tools: S3, Glue, Redshift, Lambda, Step Functions.
Strong problem-solving skills and ability to work independently within a cross-functional team.
Strong SQL and Python skills for data transformation and automation.
Hands-on experience working with various data sources, including structured and unstructured data.
Solid grasp of data warehousing concepts, data modeling, and modern ELT/ETL practices.
Experience in building data warehouse for a large enterprise.
Experience with Power BI, Snowflake on AWS, or Databricks.
Understanding of AWS-based data security and governance best practices.
Familiarity with DevOps practices

Interested candidates please click Apply.

Please note that only shortlisted candidates will be notified. EA Registration No: R1655133 Links HR Singapore Pte Ltd | EA License No: 09C5322

Senior Data Engineer