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Sr Python Full Stack Developer-Data Applications (hybrid)

Job Description - Sr Python Full Stack Developer-Data Applications (hybrid)

Description

We are looking for a Senior Python Full-Stack Developer / Data Applications Engineer with 5+ yearsof Python development experience, strong expertise in Snowflake and REST APIs, solid AWS fundamentals, and proven experience using AI-assisted and agentic coding tools such as Claude Code, Cursor, or GitHub Copilot in a production environment.



Requirements
  • 5+ years of Python development — pandas, requests, openpyxl, regex as daily tools
  • Solid Snowflake SQL — joins, CTEs, window functions, write operations (INSERT, MERGE, TRUNCATE/INSERT)
  • REST API experience — OAuth2, pagination, rate limiting, JSON/XML parsing
  • Full-stack capability — Python backend (Flask or FastAPI) with HTML/JS frontend; able to build and ship a working web application end to end
  • AWS fundamentals — S3 read/write, Lambda or EC2 execution, Secrets Manager or Parameter Store
  • Demonstrated experience with AI-assisted development — using LLMs (Claude, Copilot, GPT-4, or equivalent) as active co-authors in a production engineering context, not just for autocomplete
  • Hands-on experience with agentic coding tools — Claude Code, Cursor, Devin, or similar — directing autonomous AI execution for real deliverables
  • Comfort working from existing workflow documentation to rebuild logic in a new stack
  • Git proficiency — branching, PRs, versioned releases

Strong Plus:

  • Microsoft Graph API — SharePoint file writes, list operations, and email dispatch
  • Experience building self-service data tools or internal ops tooling for non-technical users
  • Familiarity with Alteryx Designer (understanding what you're replacing is a meaningful head start)
  • Workflow orchestration tools — Airflow, Prefect, Step Functions, or similar
  • React or Vue for more complex frontend components
  • KNIME Analytics Platform familiarity — relevant for the analyst self-service tool decision
  • Data quality libraries — Great Expectations, phone numbers, email-validator
  • Experience decomposing complex engineering problems into prompt sequences for agentic AI execution
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