Live opening · Posted 26 days ago
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About the role
Description supplied by the original job listing.
Azure Data Engineer with strong ADB (PySpark/Python), ADF; exposure to Snowflake; insurance domain basics; excellent communication; independent contributor; and effective use of GenAI tools (usage: Claude code/Claude skills/Genie) for productivity and quality.
Responsibilities:
Ingest from varied sources (APIs, DBs, and flat files) into ADLS; design medallion/layered data models.
Integrate with Snowflake (staging, modelling, performance tuning).
Ensure data quality, observability, and reliability (DQ checks, lineage, and alerting).
Requirements:
Basic to intermediate knowledge of Snowflake integrations.
4-9 years in data engineering; strong ADB (PySpark/Python) and ADF. Build and optimize scalable ETL/ELT pipelines in Azure Databricks (PySpark/Python). Hands-on with ADLS, Delta Lake, Spark performance tuning, partitioning, Z-Ordering, and caching.
GenAI-assisted development: practical experience using prompts to generate/accelerate code, tests, SQL, and documentation; ability to evaluate and safely adapt AI outputs. (IMPORTANT).
Orchestrate workflows using Azure Data Factory; manage CI/CD and environments, and secrets management (Key Vault).
Strong hands-on SQL experience.
Excellent communication and ability to work independently and with cross-functional teams. (IMPORTANT).
Basic understanding of the insurance domain (policy, claims, underwriting, risk). (must-have).
Experience
4-8 yrs
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