Databrick Data Engineer

Job description

**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 - Strong SQL and data modelling - Airflow / ADF / dbt - Git and CI/CD - Data governance, security and lineage