Senior Azure 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 analytics, artificial intelligence, and digital transformation solutions. They support a diverse portfolio of international clients across various industries by leveraging cutting-edge engineering and data-driven strategies. With a massive global workforce, they are at the forefront of driving digital innovation at scale.
About the role.
We are seeking a highly skilled Senior Azure Databricks Data Engineer to design, develop, and optimize scalable data platforms. You will play a critical role in building robust ETL/ELT workflows and implementing advanced Lakehouse architectures to support enterprise-level analytics and AI initiatives. This is a hybrid role focused on delivering high-performance data products in a collaborative, fast-paced environment.
What you will do.
- Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and cloud-native services.
- Build and optimize complex ETL/ELT workflows for large-scale structured and unstructured datasets.
- Develop sophisticated data models and implement rigorous data quality, validation, and governance frameworks.
- Integrate data from multiple sources into a unified Lakehouse architecture to support business intelligence.
- Optimize Spark jobs and Databricks workloads to ensure maximum performance, scalability, and cost efficiency.
- Implement security controls, access management, and data governance policies using Unity Catalog.
- Collaborate with cross-functional analytics and AI/ML teams to deliver trusted, high-impact data products.
- Support CI/CD, DevOps, and infrastructure automation practices to streamline deployment cycles.
What you bring.
- 9-15 years of professional experience in Data Engineering and Data Warehousing.
- Minimum 5+ years of hands-on experience with Azure Data Engineering technologies.
- Minimum 4+ years of hands-on experience with Azure Databricks and the Spark ecosystem.
- Proficiency in Python, SQL, and Delta Lake for big data processing.
- Strong understanding of data lake, lakehouse, and cloud-native architecture patterns.
- Experience with Unity Catalog, Microsoft Fabric, and data governance tools like Purview.
- Familiarity with real-time streaming solutions such as Kafka or Azure Event Hubs.
- Bachelor's or Master's degree in Computer Science, Information Technology, or a related field.
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