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 Qualified

📌 Databricks Lead – Delivery & Engineering (India)
🏢 Jade Global
📍 India