Roles & Responsibilities
- 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 practicesInterested 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
Tell employers what skills you have
Version Control
Quality Control
Data Modeling
Ability To Work Independently
Pipelines
Hadoop
Data Transformation
ETL
Data Governance
Data Engineering
SQL
Python
Data Architecture
S3
Power BI
Data Warehousing