(Senior) Data Analyst (m/f/n)

InPost is a leading e-commerce out-of-home platform in Europe, founded in 1999 by Rafał Brzoska. The company operates nearly 60,000 Paczkomatów® and about 35,000 PUDO points across nine European countries, offering parcel delivery, courier services, and fulfillment for e-commerce partners. Their solutions emphasize cost-effective, flexible, contactless, and environmentally friendly parcel delivery.

• Minimum 5 years of experience in data analysis, business intelligence, or related fields.
• At least 3 years in strategic analyses influencing business decisions.
• Experience in consumer analysis, marketing data, or mobile app data.
• Practical and advanced experience (minimum 4 years) in PySpark, SQL, or Python.
• High operational efficiency in a dynamic environment.
• Ability to navigate complex BI stacks and quickly access relevant data sources and reports.
• Higher education in quantitative or related fields such as Mathematical Methods, Mathematics, Big Data, Computer Science, Data Science, Statistics.
• At least 2 years presenting analysis results and recommendations to business stakeholders at director level.
• Knowledge of the Databricks platform and big data technologies.
• Basic knowledge of cloud technologies like Azure, AWS, or Google Cloud.
• Strong skills in structuring complex problems and data-driven conclusions.
• Proactive problem identification and solution seeking.
• Very good organizational skills and independence.
• English language proficiency at least at B2 level.

Nice to have:

• Experience with consumer segmentation and Data Science projects.
• Experience creating data objects and with Data Engineering.
• Experience with data visualization tools like Power BI or Tableau for dashboard creation.
• Experience in e-commerce analytics.

• Perform advanced reporting and in-depth data analysis integrating consumer, e-commerce, and application analytics using pyspark/SQL on Databricks, and present insights and solutions.
• Analyze data from multiple sources (frontend and backend) to detect trends and patterns.
• Translate business requirements into analytical needs and define data models.
• Independently identify areas for analysis and propose study scopes and methods, sometimes proactively before business requests.
• Prepare cyclical advanced reports and visualizations for the marketing team to monitor activity effectiveness.
• Conduct iterative data analysis including understanding, transforming, and aggregating data to establish key performance indicators per specific projects.
• Determine data availability in the data lakehouse and identify and define necessary data structures collaboratively with the Data team; debug and report errors needing correction.
• Visualize data using Power BI or collaborate on dashboard development.
• Act as a consultant in analytic matters.