Senior Databricks Data Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a leading global provider of data analytics and digital transformation services, specializing in software solutions that drive business intelligence. With a strong focus on innovation, they support enterprise-level clients across various industries in navigating complex data landscapes. Their culture emphasizes technical excellence, continuous learning, and collaborative problem-solving.
About the role.
We are looking for a Senior Databricks Data Engineer to design, develop, and optimize scalable data platforms using the Databricks Lakehouse architecture. You will play a critical role in building robust ETL/ELT pipelines, implementing data governance, and supporting AI/ML initiatives. This position offers the opportunity to work on large-scale data projects within a hybrid work environment.
What you will do.
- Design, develop, and maintain high-performance data pipelines using Databricks, Apache Spark, and PySpark.
- Build and optimize complex ETL/ELT workflows to process large-scale structured and unstructured data.
- Implement and manage data governance, security, and access control frameworks using Unity Catalog.
- Develop data models and establish data quality, validation, and lineage standards.
- Optimize Spark jobs and Databricks workloads to ensure performance, scalability, and cost efficiency.
- Collaborate with cross-functional teams to integrate data into a unified Lakehouse architecture.
- Support CI/CD, DevOps practices, and infrastructure automation to streamline deployment processes.
- Troubleshoot and resolve data pipeline issues while maintaining comprehensive technical documentation.
What you bring.
- 6–8 years of professional experience in Data Engineering and Data Warehousing.
- Hands-on expertise with Databricks, Apache Spark, PySpark, and Spark SQL.
- Proficiency in Delta Lake, Unity Catalog, and modern data governance tools.
- Strong programming skills in Python and SQL.
- Experience with ETL/ELT frameworks, data modeling, and real-time event streaming (Kafka).
- Knowledge of AI/ML pipeline integration, MLOps, and data quality tools like Great Expectations or Deequ.
- Familiarity with cloud platforms (Azure/AWS/GCP) and Snowflake.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
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