Senior Data Engineer (Azure)

Fractal • Python • SQL • ETL/ELT • 1 month ago
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Salary
≈ $25k – $48k per year (Estimated)
Location
Remote (India)
Seniority
Senior · 4+ years exp
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Fractal

Fractal is a global artificial intelligence and analytics firm headquartered in New York, United States, and founded in 2000. The company provides enterprise AI solutions, decision intelligence services, and specialized products like Crux Intelligence and Eugenie.ai to help organizations scale their AI capabilities. It operates across 10 countries, serving Fortune 500 companies in sectors such as consumer packaged goods, retail, financial services, and healthcare.
fractal.ai • HQ: New York, United States • Machine Learning • LLM & Generative AI • IT Consulting • Information Technology • Decision Intelligence • Data Science • Data & Analytics • Artificial Intelligence • 1001-5000 employees • Est. 2000

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).
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