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.

Please note that the working hours for this job would be 5PM to 2AM IST.

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 Formation

Experience 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.

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