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InPost

Data Analytics Consultant (m/f/n)

InPost
Poland · Full-time · Mid-Senior
InPost Group is an innovative European out-of-home deliveries company, revolutionizing the way parcels are delivered to customers. With operations across several countries, our network of intelligent lockers (Paczkomat®) provides customers with a fast, convenient, and secure delivery option. Our mission is to provide best-in-class user experience for merchants and consumers. "Simplify everything" – redefining e-commerce logistics. We work by innovating the market with constant technological research and with meticulous attention to the customer.

The Data & AI department is seeking a Data Analytics Consultant to join our Team. In this role, you will be responsible for analyzing vast volumes of real-time data from diverse systems, including campaigns data, product and customer analytics, sales performance, logistics processes, and similar topics relative to InPost Group products.

Technologies, you will encounter in your daily work: Apache Spark in Databricks, Python\PySpark, SQL, kafka, Power BI, GitLab, Google BigQuery, DBT.

Job Description

On a daily basis you will:

  • 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 recommendation about business critical areas and processes.
  • Design, develop, and extend our data model layers that support optimized and scalable calculations and visualizations of successful analytics outcomes.
  • Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale data environment. Maintain and advocate for these standards through code reviews.
  • Collaborate with cross-functional teams including Data Engineers, Data Scientists, and Business Analysts to deliver integrated data solutions.
  • Prototype and coordinate data visualizations.

Qualifications

Which skills should you bring to the pitch:

  • Min 3 years of experience in an analytical role handling vast volumes of data in (preferably in domains such as Marketing, Logistics, Customer or Sales).
  • 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, Bash scripting to manage Git repositories.
  • Proven ability to pull insightful and actionable conclusions from complex data and communicate recommendations to business stakeholders clearly and concisely.
  • Comprehensive understanding of the technical aspects of data warehousing, including dimensional data modeling and ETL/ELT processes.
  • Ability to translate business needs into data models.
  • Strong understanding of real-time data: ability to request and handle data from both backend and frontend systems, including internal and external platforms.
  • Self-motivated and self-managing, with the ability to work independently and mange multiple tasks simultenously.
  • Strong interpersonal skills with the ability to collaborate effectively with cross-functional teams
  • Fluency in English: verbal and written.

It would be awesome if you have:

  • Experience in working with Apache Spark in Databricks.
  • Familiarity with cloud-based data platforms (e.g. GCP, Azure, AWS).
  • Familiarity with modern data building tools like Apache Airflow, DBT.
  • Familiarity with data visualization tools such as PowerBI/Tableau/Looker.
  • Knowledge of data governance principles and practices.
  • Ability to thrive in a highly agile, intensely iterative environment.

Key Skills

Ranked by relevance

apache spark sql data visualization data warehousing data analysis power bi gitlab kafka cloud bash git aws gcp ai
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Country Guide

Poland

Fast-growing Central European IT hub

Posted
Jan 20, 2026
Type
Full-time
Level
Mid-Senior
Location
Cracow
Company
InPost

Industries

Software Development IT Services IT Consulting

Categories

Production Distribution Engineering

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