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

InPost revolutionized package delivery in Poland's e-commerce and is now one of the leading out-of-home e-commerce platforms in Europe. Founded in 1999 by Rafał Brzoska, it offers delivery services via nearly 60,000 Paczkomaty® machines and almost 35,000 PUDO points across nine European countries. InPost also provides courier-to-door and fulfillment services for e-commerce partners. Their Paczkomaty machines offer consumers a cheaper, more flexible, convenient, contactless, and environmentally friendly delivery option.

• Minimum 5 years of experience in data analysis, business intelligence, or related fields
• At least 3 years in strategic analyses influencing business decisions
• Experience with consumer, marketing, or mobile application data analysis
• Practical and advanced experience (minimum 4 years) with PySpark, SQL, or Python
• High operational efficiency in a dynamic environment
• Ability to navigate complex BI stacks and swiftly locate appropriate data sources and reports
• Higher education in Quantitative and Qualitative Methods, Mathematics, Big Data, Computer Science, Data Science, Statistics, or related fields
• Minimum 2 years presenting analysis outcomes and recommendations understandably to business stakeholders, including directors
• Familiarity with Databricks and big data technologies
• Basic knowledge of cloud technologies (Azure, AWS, Google Cloud)
• Ability to structure complex problems and draw data-driven conclusions
• Proactivity in problem identification and solution seeking
• Very good organizational skills and independence
• English proficiency at least at B2 level

Nice to have:

• Experience in consumer segmentation or Data Science projects
• Experience creating data objects/data engineering
• Experience with data visualization tools (e.g., Power BI, Tableau) for dashboard creation
• Experience in e-commerce analytics

• Advanced reporting and in-depth analysis of consumer, e-commerce, and application analytics data using PySpark/SQL in Databricks, presenting findings and solutions
• Analyzing data from multiple sources (frontend and backend) to detect trends and patterns
• Translating business requirements into analytics needs and defining data models
• Independently identifying analysis areas and proposing research scope and methods
• Preparing cyclical advanced reports and visualizations for the marketing team to monitor campaign effectiveness
• Iterative data analysis, including understanding, transformation, and aggregation to establish KPIs per project
• Assessing data availability in the data lakehouse, collaborating with Data team to define necessary data structures, debugging errors, and reporting for improvements
• Data visualization using Power BI or collaborating in dashboard development
• Acting as a consultant