Key Responsibilities
Design, develop and maintain scalable data engineering solutions using Apache Spark and Scala.
Build and manage data pipelines using Airflow and related orchestration technologies.
Work extensively with Hive, Kubernetes, Docker and GitHub Actions.
Develop and optimize data solutions using Apache Iceberg.
Design and implement data engineering solutions on Azure Databricks.
Work with ADLS, ADF, Delta Lake, Databricks Jobs & Pipelines, Lakeflow Connect and Unity Catalog.
Work with both Classic and Serverless Databricks Compute settings.
Implement scalable, reliable and high-performance data pipelines.
Follow CI/CD and DevOps best practices using GitHub Actions.
Explore and implement AI-assisted development practices across SDLC and data engineering.
Collaborate with cross-functional teams to deliver innovative data solutions aligned with business requirements.

Must-Have Skills
Spark, Scala, Airflow, Hive




Azure Databricks, ADLS, ADF, Delta Lake
Kubernetes, Docker, GitHub Actions

Strongly Preferred Skills
Apache Iceberg
Databricks Jobs & Pipelines
Lakeflow Connect
Unity Catalog
Databricks Classic & Serverless Compute
Azure Data Engineering
CI/CD
AI-assisted SDLC / AI for Data Engineering

Candidate Profile
6+ years of overall experience in Data Engineering.
Robust hands-on experience with Spark and Scala.
Valuable experience in Azure Databricks ecosystem.
Strong understanding of data pipelines, orchestration and distributed data processing.
Experience with containerization and DevOps tools.
Ability to work from Whitefield office, Bangalore, 3 days per week.
Candidates should be available for the Saturday interview.

📌 Senior Data Engineer Spark Scala Azure Databricks Bengaluru
🏢 Quess
📍 Bengaluru