Databricks Lead – Delivery & Engineering

Jade Global; Maharashtra; On-site; INR 2,000,000 - 3,000,000; Full time

Job summary

Jade Global is looking for a Databricks Lead in Maharashtra, India. This role involves leading hands-on Databricks delivery while ensuring adherence to CoE standards. Key responsibilities include managing engineering teams, optimizing Spark and Delta Lake pipelines, and designing data platforms using Databricks Lakehouse. Candidates should have 10-12 years of data engineering experience with a minimum of 3-5 years of hands-on Databricks experience, along with expertise in data modeling and performance tuning.

Qualifications

• 10-12 years in data engineering.
• 3-5 years hands-on Databricks experience.
• Deep expertise in Databricks and Apache Spark.

Responsibilities

• Lead Databricks engineering teams.
• Build and optimize Spark & Delta Lake pipelines.
• Design and implement end-to-end data platforms using Databricks Lakehouse.

Skills

Databricks expertise

Apache Spark

Delta Lake

PySpark / Spark SQL

Lakehouse architecture design

Data modeling

Performance tuning

Cloud-native data engineering

Job description

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