Mid-Level Data Visualization Analyst (Python)

We are a fast-growing software development, data science, and data engineering consultancy, and we are expanding our team to deliver large, complex projects with real impact.

Here, good data isn't what looks nice on a slide: it's what turns into decisions. We turn robust pipelines into interactive visualizations, data applications, and reliable metrics that enterprise clients actually use to change the direction of their business. This applies even when traditional BI falls short.

If you like going beyond the chart — understanding the problem, processing data in Python, building the right visualization in code, and making the numbers reliable end to end — come with us. 👇

✅ What you'll do

• Build and evolve dashboards and data applications in Python (Streamlit, Dash, or similar), interactive, performant, and ready for business users
• Develop custom and interactive visualizations with Python libraries (Plotly, Altair, Matplotlib/Seaborn)
• Prepare the data layer for visualizations using SQL and pandas/Polars: extraction, transformation, metric calculations, and aggregations at the right granularity
• Translate business questions into analyses, metrics, and actionable indicators
• Ensure the quality and reliability of the numbers: validation, reconciliation, automated tests, and documentation of rules
• Apply best practices in data storytelling and dashboard UX (clarity, hierarchy, decision focus)
• Write clean, modular, and reusable code (visualization components and templates), with Git version control, code review, and application deployment
• Collaborate with Data Science, Data Engineering, Analytics, and Product teams
• Document metric definitions, data dictionaries, and visualization standards

🎯 Requirements

• Hands-on experience with Python development for data: pandas (or Polars), code organized in modules and functions, virtual environments, and dependency management
• Experience building visualizations with Python libraries (Plotly, Matplotlib/Seaborn, Altair) and data applications with Streamlit, Dash, or similar
• Strong SQL (joins, CTEs, window functions, performance)
• Data modeling for analytics (star schema, granularity, relationships)
• Git and development best practices: branches, pull requests, code review, and testing (pytest)
• Strong analytical skills: structuring problems, finding patterns, and generating insights
• Data storytelling skills and attention to UX/design of dashboards and applications
• Nice to have: Power BI (or another BI tool), Databricks environment, application deployment (Docker, Azure/AWS/GCP), APIs with FastAPI/Flask, geospatial visualization (GeoPandas, Folium, pydeck), front-end basics (HTML/CSS/JS), and a public portfolio (GitHub, Streamlit Community Cloud, or similar)

💡 What you'll find here

• Challenging projects with large companies and real data
• A fast-growing environment with room for ownership and growth
• A team culture: collaboration, autonomy, delivery, and quality
• A modern Python and cloud stack, with real encouragement for automation and engineering best practices