
Lead Azure Data Engineer
1 day ago
This is a senior technical role with high expectations.
The consultant must be extremely hands-on, technically strong in Azure and Databricks, and capable of delivering high-quality solutions with speed and precision.The ideal candidate is a hands-on problem solver who ensures efficiency in his own work while also helping the wider team become more productive and technically stronger.Key ResponsibilitiesDesign, develop, and optimize data pipelines using Azure and Databricks.Hands-on work with Databricks Asset Bundles (DABs) for CI/CD and environment management.Build and manage scalable ELT/ETL workflows with Databricks, Delta Lake, ADF, and other Azure services.Continuously adopt and apply new Databricks features to accelerate delivery.Optimize Spark, SQL, and Python code for performance and scalability.Apply software engineering best practices (e.g., TDD, CI/CD, modular design, code reviews) to ensure a robust, maintainable, and strategic data ecosystem.Mentor team members to improve overall team productivity and technical capability.Deliver in a fast-paced environment with quick turnaround expectations.Required Skills & Experience8+ years in Data Engineering with at least 5 years hands-on in Azure & Databricks.Strong expertise in:Databricks (Delta Lake, Databricks SQL, Workflows, Databricks Asset Bundles, MLflow basics, unity catalog)Azure Data Services (ADF, Azure Synapse (good to have), Azure Data Lake, Azure SQL)Python, SQL, Spark (with proven performance optimization skills)Strong knowledge of modern data architectures (Lakehouse, governance).Track record of efficient delivery and helping teams accelerate execution.Soft Skills & AttributesEfficiency-driven mindset – focused on speeding up both personal and team delivery.Strong communicator within the team, able to share knowledge and mentor effectively.Highly motivated, proactive, and results-oriented.Ability to work in a fast-paced environment with quick turnarounds.Team-first approach – drives collective improvement and efficiency.Preferred SkillsExperience with AI-driven development (e.g., Cursor.ai, Git Hub Copilot, or similar tools) to accelerate coding, improve productivity, and maintain high-quality implementations.Exposure to Generative AI in Databricks (LLMOps, Model Serving, Mosaic ML, vector search) – good to have.Work HoursMust have 5–6 hours daily overlap with USA team (EST time zone) for collaboration.
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