We are hiring for both Databricks Data Engineers and Azure Data Engineers. Candidates with expertise in either domain, or a combination of both, are encouraged to apply. Please ensure your skills and experience are accurately reflected in the screening responses so your profile can be assessed for the appropriate role.

Role & responsibilities
Design, develop, and support data pipelines using Databricks and PySpark
Work on batch and streaming data processing using Apache Spark
Build and manage data solutions using Delta Lake, ensuring data reliability and consistency
Support production systems, troubleshoot issues, and resolve incidents independently
Contribute to migration initiatives to contemporary, cloud-based data platforms
Collaborate with onshore and offshore teams on solution design and deliver

Skillset
Databricks solid, hands-on, core experience
Experience working on Azure cloud environments
Apache Spark (deep understanding; not theoretical)
PySpark
Delta Lake
Spark SQL
Distributed data processing concepts




Cloud-based data platforms Experience with distributed storage (e.g. ADLS or equivalent)
Python (via PySpark) Focus on data processing concepts rather than framework development

GoodtoHave Skills
Azure Data Factory (ADF)
Azure SQL
Event Hubs
Synapse Analytics
Unity Catalog
Delta Live Tables

Experience Expectations
Meaningful, recent hands-on experience with Databricks is mandatory
Candidates with 5+ years of strong Databricks-focused experience are acceptable
Superficial, training-only, or very recent Databricks exposure is not sufficient

Technical Maturity Expectations
Solid understanding of up-to-date data engineering mindsets
Distributed systems over traditional RDBMS concepts
Comfortable handling production scenarios independently
Able to clearly explain design decisions and trade-offs during interviews
Demonstrates problem-solving ability beyond tool familiarity

📌 Senior Data Engineer Hyderabad
🏢 Cognizant
📍 Hyderabad