Databricks Lead – Delivery & Engineering

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 Deep expertise in Databricks, Apache Spark, Delta Lake Strong hands-on experience with PySpark / Spark SQL  (core, SQL, streaming) Experience designing Lakehouse architectures Strong understanding of data modeling, data quality, and lineage Databricks platform features Cloud-native data engineering Performance tuning & troubleshooting Certifications (Preferred) Databricks Data Engineer Associate and Professional