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Tier-1 employer, common Data Engineer title, metro locations, and broad Databricks/PySpark requirements increase competition.
Technical data-engineering skills are transferable across industries but favor enterprise analytics experience.
Strong mandatory Databricks, PySpark, Delta Lake and managerial expectations imply high shortlisting strictness.
Design and implement scalable data pipelines and Lakehouse architectures on Databricks for enterprise analytics.
Develop and optimize Delta Lake tables and PySpark applications, including incremental processing and performance tuning.
Collaborate with data architects, stakeholders, and platform teams to deliver high-quality data products adhering to governance and best practices.
Strong hands-on experience with Databricks, PySpark, and SQL for data engineering.
Experience implementing Medallion Architecture (Bronze, Silver, Gold layers) and managing Delta Lake solutions.
Role based in Pune/Gurugram with hybrid work requiring at least three days per week onsite.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in scalable cloud-native data platform development with knowledge of Lakehouse and Delta Lake principles.
Skilled in data quality, governance, monitoring, and implementing CI/CD automation in data pipelines.
Comfortable working in a hybrid environment collaborating closely across functions for data modernization and migration.