Role Description
This role focuses on building and maintaining data pipelines and analytics infrastructure on AWS. You will work daily with S3, Glue, Redshift, Athena, Lake Formation, Airflow, SNS / SQS, and Postgres to make high-quality data available to analytics and ML teams.
- Develop and maintain ETL / ELT jobs using AWS Glue and SQL / Python.
- Help manage an S3-based data lake, organizing data for efficient querying via Athena and Redshift.
- Build, schedule, and monitor data workflows using Apache Airflow (or a similar tool).
- Apply Lake Formation policies to secure and govern data access.
- Work with Postgres / PostgreSQL for operational and analytical use cases as needed.
- Implement SNS / SQS-based notifications and event-driven flows within pipelines.
- Collaborate with analytics and ML teams to understand data needs and deliver robust datasets.
- Contribute to code reviews, documentation, and ongoing data quality checks.
Qualifications
2+ years of experience as a Data Engineer or in a similar data-focused role.Hands-on experience with AWS data tools such as :S3, Glue, Redshift, Athena, Lake FormationExperience scheduling and managing pipelines with Airflow (or equivalent orchestration tool).Solid SQL skills and familiarity with Postgres / PostgreSQL.Understanding of data modelling, partitioning, and performance optimization.Comfort working in a fully remote environment with Git-based workflows and CI / CD.Nice to have :
Experience with data quality frameworks or monitoring tools.Exposure to BI tools or ML / analytics workflows.