Job Title

Role DescriptionThis 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.Qualifications2+ 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.