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Tier-1 employer, generic software title, and metro location increase candidate competition.
Data engineering skills (ETL, PySpark, Databricks) are readily transferable across industries.
Explicit minimum experience plus mandatory Azure/Databricks/PySpark tooling raises shortlisting rigidity.
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Define and support data solutions for Data Management & Analytics, ensuring compliance with data governance and privacy regulations.
Develop, test, and release ETL processes, data integrations, and data updates for local Data Warehouse and Datamarts.
Collaborate with stakeholders to ensure data quality, accessibility, and timely resolution of data-related risks or issues.
Minimum 2 years of experience in Data Engineering.
Strong hands-on skills in Microsoft Azure Data platform, including Databricks, Data Factory, Pyspark, MS SQL, and ADLS Gen-2.
Understanding of ETL processes and data warehousing concepts.
Work Experience Required: At least 2 years in Data Engineering. Notice period: Not explicitly mentioned in the JD.
Experienced working in Azure cloud environments with scalable and reusable data ingestion frameworks.
Capable of analytical troubleshooting to maintain data quality and timely issue resolution under project cycle constraints.
Comfortable collaborating with multiple stakeholders, including cross-departmental teams and external suppliers, to maintain data governance and policy compliance.