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: Robust 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.

📌 Data Engineer (Hyderabad)
🏢 Elfonze Technologies
📍 Hyderabad