Role & responsibilities
Design, build and maintain scalable ETL/ELT pipelines using Databricks, PySpark, Spark SQL and Delta Lake.
Implement Lakehouse solutions using Bronze/Silver/Gold architecture.
Optimise Spark jobs, clusters and workloads for performance and cost.
Build Databricks Workflows/Jobs and integrate with Airflow, ADF or equivalent orchestration tools.
Implement data-quality checks, monitoring and observability.
Support ML feature pipelines and MLflow-based workflows.
Work with Unity Catalog for governance, access control and lineage.
Develop robust data models with business and analytics teams.
Support Git-based CI/CD and Databricks Repos.
Troubleshoot production data-pipeline issues and perform root-cause analysis.

Preferred candidate profile
5 to 8 years of Data Engineering experience
Minimum 2 to 3 years of hands-on Databricks experience
PySpark
Spark SQL
Python
Delta Lake
Lakehouse / Medallion Architecture
Azure Databricks / AWS / GCP
Unity Catalog
Databricks Workflows / Jobs
Spark performance and cluster optimisation
Solid SQL and data modelling
Airflow / ADF / dbt
Git and CI/CD
Data governance, security and lineage

📌 Databrick Data Engineer Mumbai
🏢 BDO India
📍 Mumbai