Senior Data Engineer (Azure)
Fractal Analytics · Bengaluru · onsite · Posted 82d ago
Not disclosed4–8 yrsfulltimeSourced from
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About this role
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).
Sourced from instahyre
Skills
Apache SparkclaudeDatabricksPythonSQLAzure Data FactorySnowflakeETLADBADFPysparkAzure DatabricksMicrosoft Azure
About Fractal Analytics

Fractal Analytics
Analytics & KPO
5.2k+
employees
2000
26 years old
Mumbai, Maharashtra
India
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Fractal Analytics helps global Fortune 100 companies power every human decision in the enterprise by bringing analytics and AI to the decision.
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