Parameter
Databricks Engineer (5+ Years)
Databricks Engineer (3–4 Years)
Data QA Engineer (Modern Data Platform)
Experience
5+ Years
3–4 Years
3–7 Years
Location
Pune / Hyderabad
Pune / Hyderabad
Pune / Hyderabad
Work Model
Hybrid (3 Days WFO, 2 Days WFH)
Hybrid (3 Days WFO, 2 Days WFH)
Hybrid (3 Days WFO, 2 Days WFH)
Deployment
Immediate
Immediate
Immediate
Job Summary
Design, develop, and optimize scalable data engineering solutions using Databricks and Apache Spark.
Develop and maintain ETL/ELT pipelines and support enterprise data engineering initiatives using Databricks.
Validate Modern Data Platform implementations with a focus on Databricks and Snowflake through end-to-end data testing.
Key Responsibilities
Design and develop ETL/ELT pipelines
Build Spark applications (PySpark/Scala)
Optimize Spark jobs
Work with Delta Lake & Unity Catalog
Integrate cloud data sources
Ensure data quality and governance Develop ETL/ELT pipelines
Build PySpark applications
Write and optimize SQL queries
Work with Delta Lake
Monitor production pipelines
Support data migration and transformations Validate ETL/ELT pipelines
Perform source-to-target data validation
Test business rules and transformations
Validate Snowflake implementations
Execute SQL-based testing
Perform regression/integration testing
Track defects using Jira
Mandatory Skills
5+ years Data Engineering experience
Databricks
Apache Spark (PySpark/Scala)
Advanced SQL
Delta Lake
Azure/AWS Databricks
Git & CI/CD
Airflow/ADF 3–4 years Data Engineering experience
Databricks
PySpark
SQL
Delta Lake
Azure/AWS Cloud
Git & CI/CD 3–7 years Data QA/ETL Testing experience
SQL
Databricks Testing
Snowflake Validation
ETL/ELT Testing
Data Reconciliation
Jira
Preferred Skills
Snowflake, Azure Data Factory, AWS Glue, DevOps, Agile
Snowflake, Azure Data Factory, Airflow, Data Lake Concepts
PySpark, Azure Data Factory, Airflow, Test Automation, Agile
