Principal Data Management Strategist

Company Description

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.    

InPost Group is a publicly traded company, with a market capitalization of about $5 billion as of March 2023. With over 10,000 employees worldwide, InPost Group is one of the largest out of home delivery providers in Europe, committed to providing sustainable and efficient delivery solutions to meet the evolving needs of customers in today's rapidly changing landscape.   

We are looking for an experienced Principal Data Management Strategist to shape how data is structured, governed, and utilized across the entire InPost Group.

This position focuses on defining the long-term direction of our data landscape - ensuring consistency, scalability, and usability of analytical data assets across regions. You will influence both strategic decisions and hands-on execution, working closely with engineering teams, business stakeholders, and leadership.

Job Description

Your key responsibilities will include:

• Designing the long-term strategy for a global analytical data model, considering the diversity of source systems and business processes across all InPost markets.

• Defining the framework and methodology for data model development, including standards, design principles, and implementation guidelines.

• Establishing and maintaining a group-wide data naming and classification strategy, harmonizing existing structures and ensuring consistent adoption across teams.

• Partnering with senior stakeholders from multiple countries and domains to identify, prioritize, and align data initiatives with business objectives.

• Acting as a subject-matter expert for modern analytical architectures, continuously evaluating emerging technologies and recommending improvements.

• Supporting data engineering and analytics consulting teams through mentoring, training, and design reviews, covering theory, tools, and best practices.

• Creating and maintaining clear, multi-layered technical documentation describing data structures, modeling rules, and architectural decisions used across the InPost Group.

• Ensuring scalability and performance of analytical solutions by guiding optimization strategies for large data volumes.

Qualifications

Required experience and skills

• Minimum 6 years of experience in data engineering or analytics engineering roles

• At least 2 years of experience in a senior or lead data architecture–focused position

• Advanced proficiency in SQL

• Strong hands-on experience with Python, Spark, Databricks, Azure, and DBT

• Openness to working with internal frameworks for standardized data object creation

• Extensive experience in designing and operating modern data platforms, including data warehouses, lakehouses, and big data ecosystems

• Strong theoretical and practical knowledge of dimensional modeling, including star schema design and the Kimball methodology

• Deep understanding of medallion architecture concepts and layered data modeling approaches

• Proven ability to deliver large-scale analytics and Big Data solutions in complex environments

• Expertise in performance optimization, including:

  • query tuning in big data environments

  • ETL and data transformation optimization

  • storage layout and partitioning strategies

• Practical experience with Parquet format and Delta Lake, including:

  • data versioning

  • storage optimization

  • ACID transactions

  • ensuring data reliability and integrity

• Solid understanding of the end-to-end lifecycle of analytical data products

• Experience working in environments using CI/CD pipelines and Git-based version control (GitLab preferred)

• Excellent communication skills and ability to collaborate across technical and non-technical teams

• Fluent Polish and English