Senior Python Data Application Engineer

We're currently looking for specialists for the position of Senior Python Data Application Engineer for our client.

If you're interested, please take a look at the job offer below.

What can we offer?

• Long-term cooperation based on Employment contract
• Work mode: Hybrid in Warsaw (2-3 days per week from office)

Key Responsibilities:

• Maintain and extend a Python application that supports portfolio analysis, inventory forecasting, launchplanning, 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 chart or table, 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, suppor tprocedures, 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 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, SQLtroubleshooting, schema understanding, and performance awareness.
• Practical experience supporting forecasting, optimization, machine learning, or applied analytics code in aproduction or business-facing environment.
• Ability to understand, document, and explain business rules and analytical calculations embedded inapplication code.
• Experience with containerized Python applications using Docker or Podman.
• Experience with CI/CD pipelines, cloud deployment practices, secrets management, and productionrelease 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.

Preferred Qualifications

• Experience with Shiny for Python, R Shiny, Dash, Streamlit, or similar reactive dashboard frameworks.
• Experience with Microsoft Entra ID, Azure AD, OAuth2, or MSAL-based authentication.
• Experience with Azure OpenAI, OpenAI APIs, or LLM-enabled application features.
• Experience with AWS services for application hosting, data engineering, analytics, security, observability, or cloud migration.
• Experience with Databricks, Spark, Delta Lake, Apache Iceberg, or lakehouse data architecture.
• Experience with Snowpark Python.
• Experience with Prophet, scikit-learn, PuLP, DuckDB, Plotly, or interactive table components.
• Experience in lottery, gaming, retail analytics, inventory planning, demand forecasting, revenue management, or similar operational analytics domains.
• Experience documenting or supporting decision-support systems where users need to understand howrecommendations, forecasts, scores, or planning outputs are calculated.
• Experience supporting applications where business rules, analytics logic, and UI behavior are tightly coupled.
• Experience establishing automated test suites for data-heavy applications using pytest or similar tools.
• Familiarity with security scanning, dependency management, code quality tooling, and productionreadiness practices.