Senior Azure Databricks 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 computer software organization known for delivering innovative digital transformation and analytics solutions. They operate at a significant scale, supporting enterprise-level clients across various industries with cutting-edge technology and data-driven insights. The company fosters a collaborative, high-performance culture that encourages technical excellence and continuous professional growth.
About the role.
We are seeking a highly skilled Senior Azure Databricks Engineer to design, develop, and optimize scalable data platforms and analytics solutions. You will play a pivotal role in building robust data pipelines, implementing Lakehouse architectures, and ensuring high-performance data processing to support enterprise-wide AI and analytics initiatives. This role offers the opportunity to work on complex, large-scale data ecosystems within a hybrid work environment.
What you will do.
- Design, develop, and maintain high-performance 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 comprehensive data quality, validation, and governance frameworks.
- Integrate data from diverse sources into a unified, scalable Lakehouse architecture.
- Optimize Spark jobs and Databricks workloads to ensure maximum performance, scalability, and cost efficiency.
- Implement robust security controls, access management, and data governance policies using Unity Catalog.
- Collaborate cross-functionally with business, analytics, and AI/ML teams to deliver trusted, high-impact data products.
- Monitor, troubleshoot, and resolve complex data pipeline issues to ensure system reliability.
- Support CI/CD, DevOps, and infrastructure automation practices to streamline deployment cycles.
What you bring.
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.
- 9-15 years of total 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 the Azure Databricks and Spark ecosystem.
- Proficiency in Databricks Lakehouse Platform, Apache Spark, PySpark, Delta Lake, SQL, and Python.
- Strong understanding of data lake, lakehouse, and cloud-native architecture patterns.
- Experience with Microsoft Fabric, Power BI, Azure Event Hubs, Kafka, and Microsoft Purview.
- Proven ability to build and maintain Machine Learning data pipelines.
- Strong analytical, problem-solving, and communication skills with the ability to lead technical initiatives.
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