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High due to Tier-1 brand, popular Data Engineer role, mid-level experience, and broad Azure Databricks skillset.
Medium because core data engineering skills transfer across industries, though insurance domain preference adds some bias.
High because the JD mandates 5-7 years plus specific Azure Databricks/Synapse and AI pipeline experience.
Design, develop, and maintain scalable ETL/ELT data pipelines using Azure Databricks or Synapse, ensuring secure and compliant data handling.
Collaborate with stakeholders and cross-functional teams to deliver AI-enabled data platforms supporting Generative AI features such as RAG, vector databases, and semantic search.
Continuously improve data engineering workflows by adopting AI-assisted tools and modern automation to enhance code quality, delivery speed, and operational efficiency.
5-7 years of professional experience as a Data Engineer with expertise in Azure Synapse or Databricks (Spark/PySpark, Delta Lake, Unity Catalog).
Strong skills in SQL and Python or equivalent for data manipulation and automation.
Bachelor's or Master's degree in Computer Science, Information Systems, or related field.
Familiarity with data governance, security, compliance frameworks, orchestration tools, and version control (GitHub) with CI/CD pipelines.
Experienced in designing and supporting data platforms particularly for AI-driven solutions including embedding models and Retrieval-Augmented Generation (RAG).
Skilled at leveraging advanced AI and automation tools such as Microsoft Copilot or Claude to optimize engineering productivity and delivery velocity.
Comfortable working in collaborative, client-facing environments and applying knowledge of distributed data processing concepts like medallion architecture and data lakehouse principles.