Role & responsibilities

- 3+ years of hands-on experience working with Databricks, Apache Spark, or related big data platforms
- Proficiency in programming languages such as Python, Scala, or SQL for data transformation and pipeline development
- Hands-on experience with Spark SQL, Delta Lake, Lakeflow Spark Declarative Pipelines and Unity Catalog
- Strong understanding of ETL/ELT workflows, data modeling, and data warehousing concepts
- Experience with cloud platforms (Azure, AWS, or GCP)
- Familiarity with CI/CD practices and version control tools such as Git
- Knowledge of data governance, data quality, and security best practices
- Excellent problem-solving, analytical, and communication skills.
- Ability to work collaboratively in an agile team workplace
- Databricks certifications are preferred

Preferred candidate profile

- Implement data ingestion, transformation,



and integration processes from various structured and unstructured data sources
- Develop, maintain, and optimize scalable data pipelines and workflows on the Databricks platform
- Collaborate with analysts and business stakeholders to understand data requirements and deliver solutions
- Ensure data reliability, quality, and security across all data engineering processes
- Troubleshoot, debug, and resolve data pipeline issues and performance bottlenecks
- Document data engineering workflows and technical designs
- Monitor and maintain data pipeline health, proactively addressing any potential issues
- Stay up-to-date with emerging data engineering technologies and best practices, especially within the Databricks ecosystem

📌 Databricks Engineer (Maharashtra)
🏢 Tata Consultancy Services
📍 Maharashtra