Data Engineer (Azure Data Factory / Databricks )
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Job description
Seeking a Data Engineer / Senior Consultant with 7 to 10 years of experience for a 12-month contract position in Hartford, CT (Hybrid setup)., * Architecture & Scalable Engineering: Design, build, and optimize highly available, scalable, and efficient data services, applications, and pipelines; guide architectural choices using cloud-native solution methodologies.
- Client & Team Leadership: Work closely with clients, enterprise architects, and development teams to align application architecture and lead end-to-end design, development, testing, deployment, and maintenance.
- Modern Data Stack Execution: Develop robust ETL/ELT workflows leveraging Azure Data Factory, Databricks, and Snowflake; enforce coding standards, CI/CD via Azure DevOps, and project guidelines to ensure code integrity.
- AI-Driven Productivity: Leverage AI productivity tools (GitHub Copilot, Cortex/CoCo, Genie) for pseudo-code generation, rapid prototyping, reverse engineering, and automated testing delivery.
Requirements
The ideal candidate will specialize in designing highly available, scalable, and optimized data solutions using Azure Data Factory (ADF), Azure Databricks, and Snowflake. This is a client-facing lead role requiring hands-on expertise with AI-assisted engineering tools (GitHub Copilot, Cortex/CoCo, Genie) for code creation, reverse engineering, and productivity enhancement, preferably within the Insurance / Reinsurance domain., * Core Experience: 7 to 10 years of dedicated experience in Data Engineering.
- Core Tech Stack: Deep hands-on expertise in Azure Data Factory (ADF), Azure Databricks, and Snowflake.
- DevOps & AI Tools: Advanced proficiency in Azure DevOps alongside practical experience using GitHub Copilot, Cortex (CoCo), or Genie.
- Domain & Soft Skills: Strong client-facing communication skills and team leadership; Insurance / Reinsurance domain background is highly preferred.
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