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Python/Spark/AI Developer

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Summary

Intermediate-to-senior developer role replatforming legacy T-SQL workloads onto Spark/PySpark and Delta Lake pipelines, while building type-safe Python REST APIs (FastAPI) and AI-enabled features. Core stack: Python 3.12, Spark, Delta Lake, pytest, Docker, Git/CI, with optional LLM and Azure exposure.

Our client is seeking an experienced Python / Spark / AI Developer to help replatform legacy T-SQL workloads onto modern Spark and Delta Lake pipelines while developing robust APIs and AI-enabled capabilities. This intermediate-to-senior role is suited to a developer who is comfortable working autonomously in a specification-driven environment and delivering production-quality, well-tested code.

Key Responsibilities

  • Build production-grade Spark/PySpark pipelines using Delta Lake.
  • Replatform legacy T-SQL logic into Spark SQL while preserving functional parity.
  • Develop modern, type-safe Python using strong testing and static-analysis practices.
  • Build REST APIs using FastAPI or equivalent frameworks.
  • Implement authentication, idempotency and reliable job-status semantics.
  • Validate migrated pipelines against legacy systems and provide evidence of output parity.
  • Work from design documents and Architecture Decision Records (ADRs).
  • Contribute tests and documentation alongside code changes.
  • Participate in Git-based, PR-driven development and CI processes.

Essential Requirements

  • 4+ years' professional Python development experience.
  • 2+ years' production experience building Spark/PySpark or comparable distributed data pipelines.
  • Strong Python 3.12 experience, including type hints, Pydantic, modern packaging and static analysis.
  • Strong Apache Spark/PySpark knowledge, including DataFrame API, Spark SQL, partitioning and performance tuning.
  • Understanding of Spark driver/executor architecture and Spark Connect.
  • Production experience with Delta Lake or equivalent lakehouse technologies such as Iceberg or Hudi.
  • Strong SQL skills and the ability to translate legacy T-SQL logic into Spark SQL.
  • Experience with MERGE operations, schema evolution, idempotent writes, hashing, surrogate keys and deduplication.
  • Strong automated testing experience using pytest.
  • REST API development experience, preferably with FastAPI.
  • Experience with Docker-based development environments.
  • Strong Git and CI/CD discipline, including linting, type-checking and automated testing.
  • Bachelor's degree in Computer Science, Engineering or equivalent experience.
  • Ability to work independently from written specifications and technical requirements.

Advantageous

  • LLM integration and AI feature development.
  • Experience with Ollama, vLLM, llama.cpp, LM Studio or hosted AI APIs.
  • Data governance, PII protection and privacy engineering.
  • Experience with Hive Metastore, Trino or Apache Ranger.
  • Azure data technologies including ADLS Gen2, Synapse/ADF, Key Vault or Service Bus.
  • Observability tools such as OpenTelemetry, OpenLineage or structured logging.
  • Data migration and output-parity experience.
  • Databricks Certified Developer for Apache Spark or equivalent certification.
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