Senior Data Engineer (Databricks)

Senior Data Engineer (Databricks)About the RoleWe are seeking an experienced Senior Data Engineer with strong hands-on expertise in Databricks to design, build, optimize, and support enterprise-scale data pipelines. This individual will play a key role in expanding and maturing our modern data platform, ensuring high-quality, reliable data is available for analytics, reporting, and downstream applications.ResponsibilitiesDesign, develop, and maintain scalable, production-grade ETL/ELT pipelines using Databricks, PySpark, Spark SQL, Delta Live Tables, and Databricks Workflows.Build and optimize data ingestion pipelines for structured, semi-structured, and streaming data across Bronze, Silver, and Gold layers.Develop reusable data engineering frameworks, transformation logic, and data quality validations.Leverage Databricks AI Genie and other native platform capabilities to improve development efficiency and accelerate delivery.Implement best practices for orchestration, monitoring, alerting, automation, and pipeline reliability.Optimize Spark jobs and SQL queries for scalability and performance.Design and implement dimensional data models (star and snowflake schemas) to support analytical workloads.Apply normalization and denormalization techniques where appropriate to balance performance and usability.Build physical data models aligned with Delta Lake and Medallion Architecture.Ensure data quality, integrity, governance, and compliance with enterprise standards.Collaborate with cross-functional teams to deliver scalable, high-performing data solutions.Required Qualifications7–10+ years of experience in data engineering.Proven experience designing, building, and deploying enterprise-scale Databricks solutions.Strong expertise with Databricks, PySpark, Spark SQL, Delta Lake, Delta Live Tables, Unity Catalog, and Databricks Workflows.Strong understanding of Medallion Architecture (Bronze, Silver, and Gold).Advanced SQL development and performance tuning experience.Experience with AWS, Azure, or GCP.Strong understanding of modern lakehouse architecture and distributed data processing.Experience with CI/CD pipelines, Git, and job orchestration tools.Deep understanding of dimensional data modeling and data warehousing concepts.Experience developing scalable, maintainable ETL/ELT frameworks in production environments.Preferred QualificationsExperience working with streaming data pipelines.Familiarity with enterprise data governance and security best practices.Experience building reusable data engineering frameworks and automation solutions.Strong problem-solving skills with the ability to optimize large-scale data workloads.