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Remote posting, popular Data Engineer title, metro Bangalore, and mid-level experience increase competition.
Core data engineering skills are broadly transferable across industries despite HR analytics emphasis.
Mandatory AWS, Airflow, SQL, data modeling skills raise filtering but no explicit years.
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Design, build, and maintain end-to-end data pipelines and analytical data models for People Analytics using AWS (S3, APIs) and Apache Airflow.
Ensure data reliability, quality, and performance by setting up data quality guardrails and troubleshooting pipeline failures.
Support backend integration for Power BI dashboards and contribute to data warehouse redesign in SAP.
Strong experience in data engineering and data modelling for analytics platforms.
Hands-on experience with AWS (S3, API integrations), Apache Airflow, and excellent SQL skills including complex transformations and optimisation.
Experience managing data warehouses or lakehouses and using version control tools like GitHub.
Bachelor’s degree in computer science, Information Systems, Business Administration, or related field. Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable, cloud-based data pipelines with operational ownership over data quality and performance.
Familiar with People Analytics or HR analytics platforms and exposure to SAP data products (BDC, Datasphere, SAP BO) is a plus.
Capable of supporting BI integrations and redesigning data warehouses to optimize analytics delivery.