Python Data Applications Engineer

Python Data Applications Engineer

Our client is seeking an experienced Python Data Applications Engineer to support and enhance a business-critical application used for portfolio analysis, inventory forecasting, launch planning, and AI-assisted reporting.

Responsibilities

• Maintain and extend a Python application that supports portfolio analysis, inventory forecasting, launch planning, and AI-assisted reporting.
• Diagnose and resolve production issues across application code, data pipelines, database queries, authentication, configuration, and deployments.
• Improve reliability by adding automated tests, integration checks, structured logging, input validation, and CI/CD quality gates.
• Support and refine forecasting, inventory projection, and optimization logic in partnership with business stakeholders.
• Translate business planning rules into maintainable algorithms, user workflows, and dashboard features.
• Explain complex analytical, forecasting, scoring, and optimization logic clearly to both business and technical stakeholders.
• Trace dashboard behavior from data source to transformation logic to rendered charts and tables, including the business meaning of key metrics and outputs.
• Own data lineage and calculation transparency for dashboard metrics, charts, forecasts, targets, and generated planning recommendations.
• Partner with business users to validate whether forecasts, optimization outputs, and portfolio metrics align with operational planning expectations.
• Secure and operationalize environment configuration, secrets management, database authentication, and identity provider integration.
• Maintain and improve containerized deployments using Docker or Podman and cloud-based release pipelines.
• Help assess and adapt the application for future AWS, lakehouse, and analytics platform migration needs.
• Refactor legacy or prototype-quality code into clearer, modular, testable components without disrupting active users.
• Create knowledge-transfer documentation, source-level walkthroughs, operational runbooks, support procedures, and release notes for technical and non-technical stakeholders.

Required Qualifications

• 6+ years of professional Python engineering experience, preferably supporting production data applications.
• Strong experience with Python, pandas, NumPy, SQL, and data transformation workflows.
• Experience building or maintaining interactive data applications using frameworks such as FastAPI, Flask, Dash, Streamlit, Shiny for Python, or similar tools.
• Strong Snowflake or cloud data warehouse experience, including secure connectivity, SQL troubleshooting, schema understanding, and performance awareness.
• Practical experience supporting forecasting, optimization, machine learning, or applied analytics code in a production or business-facing environment.
• Ability to understand, document, and explain business rules and analytical calculations embedded in application code.
• Experience with containerized Python applications using Docker or Podman.
• Experience with CI/CD pipelines, cloud deployment practices, secrets management, and production release support.
• Strong debugging skills across application, data, authentication, configuration, and deployment layers.
• Ability to inherit an early-stage or rapidly evolving codebase and improve it methodically while continuing to deliver business value.

What We Offer

• Permanent employment contract (Umowa o pracę).
• Hybrid working model (50% office-based).
• Private medical healthcare.
• Opportunity to work on a strategic data and planning platform with significant business impact.
• Collaborative environment with close interaction between business and technology teams.
• Exposure to forecasting, analytics, optimization, and cloud-based data solutions.