Source description
About the role
Databricks Lead – Delivery & Engineering1 Lead hands-on Databricks delivery , ensuring adherence to CoE standards and best practices. Key Responsibilities Lead Databricks engineering teams
Build and optimize Spark & Delta Lake pipelines
Implement Databricks Jobs, Workflows, CI/CD
Optimize performance and DBU usage
Contribute to Databricks accelerators and standards
Design and implement end-to-end data platforms using Databricks Lakehouse
Lead development of: Data ingestion (batch & streaming)
Delta Lake data modeling (Bronze/Silver/Gold)
Scalable ETL/ELT pipelines
Optimize Spark workloads for performance and cost
Ensure reliability, scalability, and observability of data pipelines
Experience 10–12 years in data engineering
3–5 years hands-on Databricks experience
Skills
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Deep expertise in Databricks, Apache Spark, Delta Lake
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Strong hands-on experience with PySpark / Spark SQL (core, SQL, streaming)
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Experience designing Lakehouse architectures
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Strong understanding of data modeling, data quality, and lineage
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Databricks platform features
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Cloud-native data engineering
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Performance tuning & troubleshooting
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Certifications (Preferred) Databricks Data Engineer Associate and Professional
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