Databricks Engineer

Databricks Engineer Experience: 7–12 yearsLocation-RemoteOverviewWe are looking for an experienced Databricks Engineer with deep expertise in designing, building, and optimizing modern data platforms on Azure and Databricks. The ideal candidate will serve as the go-to expert for Databricks platform architecture, Unity Catalog, and emerging Databricks capabilities such as Genie, Vector Search, and Agent Bricks.Key ResponsibilitiesArchitect, design, and implement scalable, secure, and high-performance data solutions using Azure and Databricks.Act as a subject matter expert on Azure Data Services and Databricks platform architecture.Design and implement POCs leveraging modern data architecture patterns (e.g., Lakehouse, Delta Lake, Medallion architecture).Build and optimize data pipelines for both real-time and batch processing, including API integrations.Support DevOps, CI/CD, and monitoring practices for data workloads.Implement self-serve data layers tailored to different user personas.Collaborate effectively with client architecture and platform teams; strong communication and leadership in technical discussions.Evaluate and experiment with new Databricks offerings (e.g., Genie, Vector Search, Agent Bricks, LakeFlow) through rapid POCs.Required Skills & Experience8–12 years of total experience in Data Engineering / Data Architecture.Strong hands-on experience with Databricks, Unity Catalog, and Azure Data Services (e.g., Azure Data Factory, Synapse, ADLS).Solid understanding of data management, governance, and security principles.Experience with Delta Lake, Lakehouse architecture, and modern ETL/ELT best practices.Familiarity with Python, PySpark, and SQL for data engineering.Exposure to real-time streaming frameworks (e.g., Kafka, Event Hubs) is a plus.Excellent communication and client-facing skills.