Required Skills:
Databricks (Must-Have): 3+ years Workspace, Unity Catalog, Delta Live Tables (DLT), Workflows/Jobs, SQL Warehouses
Delta Lake & Lakehouse: Lakehouse architecture design, Bronze/Silver/Gold patterns, ACID transactions, schema evolution
Spark & PySpark (Must-Have): DataFrame API, Spark SQL, transformations, actions, performance tuning
Streaming (Must-Have): Structured Streaming, Auto Loader for incremental ingestion
Python (Must-Have): Production-grade scripting for data engineering and automation
Azure Stack (Must-Have) ADF (orchestration), ADLS Gen2 (storage), Azure SQL (relational)
Performance Tuning: Partitioning, Z-ordering, caching, shuffle optimization, job cluster sizing

Preferred Qualifications:
Experience with Databricks Asset Bundles or CI/CD for Databricks (GitHub Actions, Azure DevOps).
Familiarity with data modeling concepts (Star Schema, Data Vault 2.0).
Exposure to Power BI / Tableau connecting via Databricks SQL.
Knowledge of Databricks cost optimization (cluster policies, spot instances, photon engine).
Databricks Certified Data Engineer Associate/Skilled is a plus.
Exposure to Agile/Scrum delivery methodologies.

📌 Data Engineer Uttar Pradesh
🏢 PwC India
📍 Uttar Pradesh