Senior Data Engineer

Quess IT Solutions; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Quess IT Solutions in Bengaluru seeks an experienced Data Engineer with 6+ years of hands-on expertise in building scalable data pipelines and modern data platforms.

The role requires strong knowledge of Spark, Scala, Airflow, Hive, Kubernetes, Iceberg, and Azure Databricks, plus CI/CD and AI integration across the SDLC to drive efficiency and business value.

Qualifications

• 6+ years of relevant experience in Data Engineering.
• Strong understanding of data engineering concepts and distributed data processing.
• Excellent communication and collaboration skills.
• Candidates must be based in or willing to relocate to Bengaluru.
• Candidates should be comfortable working from the office.
• Willingness to attend 2 technical interview rounds.

Responsibilities

• Design, develop, and maintain scalable data engineering pipelines.
• Build data processing solutions using Apache Spark and Scala.
• Develop and manage workflows using Apache Airflow.
• Work with Hive, Iceberg, Kubernetes, and Docker in modern data platforms.
• Develop and maintain CI/CD pipelines using GitHub Actions.
• Design and implement data solutions using Azure Databricks.
• Work with ADLS, Azure Data Factory (ADF), Delta Lake, Databricks Jobs and Pipelines.
• Utilize Lakeflow Connect, Unity Catalog, and Databricks Compute (Classic & Serverless).
• Implement data governance, security, and access controls using Unity Catalog.
• Optimize data pipelines and processing workloads for performance and scalability.
• Collaborate with data scientists, architects, product teams, and other engineering teams.
• Apply AI capabilities and tools across the SDLC and Data Engineering lifecycle to improve productivity, automation, and business outcomes.
• Follow engineering best practices around version control, testing, deployment, monitoring, and documentation.

Skills

Apache Spark

Scala

Hive

Docker

GitHub Actions

CI/CD

Tools

Azure Databricks

ADLS

Lakeflow Connect

Unity Catalog

Databricks Compute (Classic & Serverless)

Delta Lake

Job description

We are looking for an experienced Data Engineer with 6+ years of hands-on experience in building and managing scalable data engineering solutions. The ideal candidate should have strong expertise in Spark, Scala, Airflow, Hive, Kubernetes, Iceberg, and Azure Databricks.

The candidate should also have a good understanding of modern data platforms, cloud technologies, CI/CD practices, and the ability to leverage AI across the Software Development Lifecycle (SDLC) and Data Engineering to drive innovation and business value.

Key Responsibilities

• Design, develop, and maintain scalable and reliable data engineering pipelines.
• Build data processing solutions using Apache Spark and Scala.
• Develop and manage workflows using Apache Airflow.
• Work with Hive, Iceberg, Kubernetes, and Docker in modern data platforms.
• Develop and maintain CI/CD pipelines using GitHub Actions.
• Design and implement data solutions using Azure Databricks.
• Work with ADLS, Azure Data Factory (ADF), Delta Lake, Databricks Jobs and Pipelines.
• Utilize Lakeflow Connect, Unity Catalog, and Databricks Compute (Classic & Serverless).
• Implement data governance, security, and access controls using Unity Catalog.
• Optimize data pipelines and processing workloads for performance and scalability.
• Collaborate with data scientists, architects, product teams, and other engineering teams.
• Apply AI capabilities and tools across the SDLC and Data Engineering lifecycle to improve productivity, automation, and business outcomes.
• Follow engineering best practices around version control, testing, deployment, monitoring, and documentation.

Required Skills

Must-Have – Priority 1

• Strong hands-on experience with Apache Spark
• Scala
• Hive
• Good knowledge of Docker
• Good experience with GitHub Actions / CI-CD

Must-Have – Priority 2

• Strong experience with Azure Databricks
• ADLS
• Lakeflow Connect
• Unity Catalog
• Databricks Compute – Classic & Serverless

Must-Have – Priority 3

• Experience using AI tools/capabilities within SDLC and Data Engineering
• Ability to identify opportunities to use AI for automation, development, optimization, and innovation
• Strong problem-solving and analytical skills

Additional Requirements

• 6+ years of relevant experience in Data Engineering.
• Strong understanding of data engineering concepts and distributed data processing.
• Excellent communication and collaboration skills.
• Candidates must be based in or willing to relocate to Bengaluru.
• Candidates should be comfortable working from the office
• Willingness to attend 2 technical interview rounds.

Preferred Candidate Profile

Candidates with strong hands-on experience across Spark/Scala/Airflow and the Azure Databricks ecosystem will be given priority. Experience in modern data lakehouse technologies, containerization, CI/CD, and practical application of AI in engineering environments will be an added advantage.