(Senior) Data Analytics Consultant (m/f/n)

InPost Group is an innovative European out-of-home deliveries company operating a network of intelligent lockers (Paczkomat®) across several countries, providing fast, convenient, and secure parcel delivery. The Data & AI department focuses on analyzing real-time data from various systems related to campaigns, product and customer analytics, sales performance, and logistics processes to support InPost Group products.

• Minimum 3 years of experience in an analytical role handling large volumes of data, preferably in Marketing, Logistics, Customer, or Sales domains.
• Experience in data modeling and implementing complex data-driven solutions is a strong plus.
• Strong proficiency in Python/PySpark for data analysis, SQL for data processing, and Bash scripting for managing Git repositories.
• Proven ability to derive actionable insights from complex data and communicate recommendations clearly to business stakeholders.
• Comprehensive understanding of data warehousing technical aspects, including dimensional data modeling and ETL/ELT processes.
• Ability to translate business needs into data models.
• Strong understanding of real-time data handling from backend and frontend systems, including internal and external platforms.
• Self-motivated and able to work independently while coordinating multiple workstreams.
• Strong interpersonal skills for effective collaboration with cross-functional teams.
• Fluency in English, both verbal and written.

Nice to have:

• Ability to read or communicate in French.
• Experience with Apache Spark in Databricks.
• Familiarity with cloud-based data platforms (GCP, Azure, AWS).
• Familiarity with modern data building tools like Apache Airflow and DBT.
• Familiarity with data visualization tools such as Power BI, Tableau, or Looker.
• Knowledge of data governance principles and practices.
• Ability to thrive in a highly agile, iterative environment.

• Closely support stakeholders in making data-driven decisions.
• Work with different InPost departments and business lines.
• Gather requirements, harness large-scale, real-time data from various sources, analyze it, and prepare insights and recommendations about business-critical areas and processes.
• Design, develop, and extend data model layers that support optimized and scalable calculations and visualizations.
• Write code adhering to internal standards for style, maintainability, and best practices in a high-scale data environment.
• Maintain and advocate for coding standards through code reviews.
• Collaborate with Data Engineers, Data Scientists, and Business Analysts to deliver integrated data solutions.
• Prototype and coordinate data visualizations.