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Metro location, popular Data Engineer title, and recognizable global employer increase applicant competition despite niche Databricks skills.
Core data engineering skills are transferable, though Databricks specialization slightly narrows cross-industry fit.
Explicit 8+ years and mandatory Databricks, Spark, cloud, and Terraform skills enforce strict shortlisting.
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Build, optimize, and scale modern cloud-native data pipelines and platforms using Databricks and Apache Spark (PySpark).
Lead data migration initiatives from AWS Glue/Redshift to Databricks as part of enterprise data modernization.
Implement data ingestion, governance, security, and performance optimization, collaborating cross-functionally and mentoring junior engineers.
Minimum 8 years of experience in data engineering.
Strong hands-on expertise in Databricks, Apache Spark (PySpark), Delta Lake, SQL, and Python.
Experience with cloud-native data architectures and data pipeline development on Databricks.
Location: Pune with hybrid working arrangement.
Experienced with scalable production-grade data pipelines on cloud platforms, particularly Databricks on Azure or AWS.
Demonstrated ability to lead complex data migration and modernization projects involving AWS and Databricks ecosystems.
Comfortable working cross-functionally with analytics, AI/ML, and business teams, while mentoring junior engineers.