Python Software Engineer (Production Data & Model Services) | Middle

Опис

We are seeking a Python Software Engineer to join our Production Data & Model Services team. In this role, you will build and operate production-grade Python applications, transform data science prototypes into deployable services and collaborate with platform teams to deliver robust data pipelines and APIs. Responsibilities Build and run production-grade Python applications (APIs and batch jobs) with strong SDLC practices including code reviews, testing, CI/CD, observability and documentation Develop robust data pipelines (batch and near-real-time) reading and writing governed storage with Parquet/columnar formats and approved patterns Transform quant and data science prototypes into deployable packages/services (typed, modular, versioned) Expose scoring and analytics via APIs or scheduled jobs rather than notebook-only deliverables Collaborate with platform teams on Databricks/Spark connectivity Optimize PySpark workloads when needed Ensure release discipline through Git workflows, automated tests and code reviews Requirements 3+ years of strong Python engineering experience including packaging (wheels/pyproject), typing and clean architecture Proficiency in error handling and performance-oriented development Proven production SDLC background with Git workflows, automated tests and CI/CD Expertise in Pandas and NumPy in production pipelines Familiarity with data formats like Parquet and governed data access patterns Experience building and operating APIs/services using FastAPI, Flask or similar frameworks Competency working in governed platform environments such as Databricks or containerized dev platforms Nice to have Skills in scikit-learn for production feature and scoring pipelines, including reproducible transforms and model packaging/versioning Background in PySpark and distributed processing Knowledge of IDE-to-Databricks workflows such as Databricks Connect

Вимоги

• 3+ years of strong Python engineering experience including packaging (wheels/pyproject), typing and clean architecture

• Proficiency in error handling and performance-oriented development

• Proven production SDLC background with Git workflows, automated tests and CI/CD

• Expertise in Pandas and NumPy in production pipelines

• Familiarity with data formats like Parquet and governed data access patterns

• Experience building and operating APIs/services using FastAPI, Flask or similar frameworks

• Competency working in governed platform environments such as Databricks or containerized dev platforms

Zakres obowiązków

• Build and run production-grade Python applications (APIs and batch jobs) with strong SDLC practices including code reviews, testing, CI/CD, observability and documentation

• Develop robust data pipelines (batch and near-real-time) reading and writing governed storage with Parquet/columnar formats and approved patterns

• Transform quant and data science prototypes into deployable packages/services (typed, modular, versioned)

• Expose scoring and analytics via APIs or scheduled jobs rather than notebook-only deliverables

• Collaborate with platform teams on Databricks/Spark connectivity

• Optimize PySpark workloads when needed

• Ensure release discipline through Git workflows, automated tests and code reviews

Seniority

• Middle

Mile widziane

• Skills in scikit-learn for production feature and scoring pipelines, including reproducible transforms and model packaging/versioning

• Background in PySpark and distributed processing

• Knowledge of IDE-to-Databricks workflows such as Databricks Connect