We are looking for an experienced Azure Databricks Data Engineer with strong hands-on expertise in Azure Cloud, Databricks, Azure Data Factory, Apache Spark, SQL, and Python. The ideal candidate will be responsible for developing, maintaining, and supporting scalable data engineering solutions while working closely with business and technical teams.

The candidate should also have hands-on experience with AI-powered coding assistants and be comfortable leveraging these tools to improve development productivity, code quality, debugging, and automation.

Design, develop, and maintain scalable data engineering solutions using Azure Cloud, Databricks, and Azure Data Factory.

Develop, configure, schedule, and monitor Databricks Jobs to support business and data processing requirements.

Develop and maintain Databricks notebooks using Python/PySpark for data ingestion, transformation, validation, and processing.

Work with Databricks Unity Catalog for data access, governance, permissions, and data management.

Design and implement data pipelines using Azure Data Factory (ADF).

Develop effective and optimized SQL queries for data extraction, transformation, validation, and analysis.

Use Apache Spark/PySpark for processing and transforming large volumes of data.

Develop automation and data-processing solutions using Python.

Monitor and troubleshoot Databricks jobs, ADF pipelines, notebooks, and production data issues.

Identify and resolve data quality, pipeline failures, performance, and operational issues.

Optimize Spark jobs, SQL queries, Databricks notebooks, and data pipelines for improved performance and scalability.

Collaborate with business stakeholders, data engineers, architects,



and other technical teams to understand requirements and deliver effective solutions.

Participate in code reviews and follow established coding, testing, documentation, and deployment standards.

Use AI coding assistants such as GitHub Copilot or similar tools to accelerate development, generate and review code, debug issues, refactor code, and improve developer productivity.

Ensure solutions are secure, reliable, scalable, and aligned with Azure and data engineering best practices.

Support production deployments, incident resolution, and continuous improvement of data engineering solutions.

Maintain technical documentation for data pipelines, Databricks jobs, notebooks, and implemented solutions.

Hands-on experience with Azure cloud

Experience with Databricks (experience in creating jobs, working with unity catalog, supporting business through notebooks)

Experience with Azure Data Factory

Hands-on experience in SQL

Experience with Apache Spark

Hands-on experience in Python

Hands-on experience with AI coding assistants

Opportunity to work on bleeding-edge projects

Competitive salary

Flexible schedule

Benefits package - medical insurance, sports

Corporate social events

Professional development opportunities

Well-equipped office

GDYN) is a leading provider of technology consulting, platform and product engineering, AI, and advanced analytics services. Fusing technical vision with business acumen, we solve the most pressing technical challenges and enable positive business outcomes for enterprise companies undergoing business transformation. A key differentiator for Grid Dynamics is our 8 years of experience and leadership in enterprise AI, supported by profound expertise and ongoing investment in data, analytics, cloud & DevOps, application modernization and customer experience.

📌 Senior Data Engineer - AI & Data (Secunderabad)
🏢 Grid Dynamics
📍 Secunderabad