Data Engineer

Job title : Senior Data Engineer Exp : 5-8 years exp Azure Databricks: Strong hands-on experience with Databricks Lakehouse Architecture, Delta Lake, Unity Catalog, Databricks Apps, Workflows/Jobs, and Databricks Asset Bundles (DAB). Real-Time Data Ingestion: Experience with Azure Event Hubs, Spark Structured Streaming, Auto Loader, Databricks Zerobus Ingest, and Delta Change Data Feed (CDF). Python & SQL: Strong proficiency in Python, PySpark, and SQL for data engineering, transformation, optimization, and automation. Configuration-Driven Framework: Experience designing reusable, modular, metadata-driven Python frameworks with configurable business rules, execution engines, and orchestration layers. Lakebase (PostgreSQL): Hands-on experience with Lakebase for operational data storage, relational data modeling, SQL development, and Lakebase-to-Delta synchronization. Databricks Lakehouse: Experience implementing Bronze, Silver, and Gold architectures, Delta tables, data transformations, and scalable analytical pipelines. Data Pipeline Engineering: Ability to design batch and streaming pipelines with error handling, retries, replay, reconciliation, and failure recovery mechanisms. Data Quality & Governance: Experience implementing validation frameworks, data quality checks, quarantine handling, audit logging, and Unity Catalog governance. Data Modeling & Historical Processing: Strong understanding of relational data modeling, source-to-target mappings, CDC, SCD Type 2, and historical data synchronization. Performance Optimization: Ability to optimize Spark workloads, SQL queries, Delta tables, job execution, and data processing costs.