Data Engineer

Elfonze Technologies; Telangana; Vor Ort; INR 1.800.000 - 2.400.000; Vollzeit

Zusammenfassung

Elfonze Technologies Pvt. Ltd. in Hyderabad, Telangana, invites a Senior Data Engineer to join our IT team.

The role focuses on building scalable data pipelines with Databricks Lakehouse, Delta Lake, and Unity Catalog, delivering Bronze-Silver-Gold data architectures, and ensuring data quality and governance. You will collaborate with cross-functional teams to design reusable frameworks and optimize Spark workloads.

Qualifikationen

• 5-8 years of data engineering experience.
• Strong hands-on Databricks Lakehouse experience.
• Proficient in Python, PySpark and SQL for data pipelines.

Kenntnisse

Azure Databricks

Python

PySpark

SQL

Databricks Lakehouse

Delta Lake

Unity Catalog

Databricks Jobs

Event Hubs

Spark Structured Streaming

Lakebase

Batch & Streaming Pipelines

Data Quality & Governance

CDC & SCD Type 2

Performance Optimization

Tools

Lakebase (PostgreSQL)

Jobbeschreibung

Job Information

• Date Opened 10/28/2026
• Job Type Full time
• Industry IT Services
• City Hyderabad
• State/Province Telangana
• Country India
• Zip/Postal Code 500001

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.