Lead a multidisciplinary data organization, hiring, developing, and establishing career frameworks while bridging legacy expertise with modern platform capabilities
Collaborate closely with analytics, product, engineering, and business teams to provide the platform foundation they depend on
Own the architecture and delivery of the enterprise data platform across cloud environments, supporting batch, streaming, structured, and unstructured data
Define and govern enterprise-level data architecture patterns and data modeling standards, applying them pragmatically across domains
Develop integration strategies for source systems to enhance data quality, prevent technical debt, and optimize access to reliable data
Establish the data product model with clear ownership, SLAs, versioning, and discoverability, shifting the team’s output from pipelines to trusted, consumable data assets
Lead the design and build of the enterprise semantic layer with canonical metrics and business definitions that serve BI tooling, AI grounding, and operational consumers from a single source of truth
Embed governance in the engineering lifecycle through data contracts, policy-as-code, lineage automation, quality checks, and access controls with auditable versioning
Build the data infrastructure required for AI/ML workloads, including feature pipelines, vector stores, embedding pipelines, and model-ready data products across all enterprise data assets

Bring experience in data engineering, architecture, and data platforms, along with a track record of leading technical teams and delivering modern, cloud-based data solutions
Have built data products with real users in mind, including managing SLAs and incorporating continuous feedback loops
Have a hands-on background in semantic layer design and apply strong analytics engineering practices
Understand how to implement governance-as-code, including data contracts, lineage, quality, and access as core engineering artifacts
Have working knowledge of AI data infrastructure, such as feature stores, vector databases, and pipelines for unstructured data
Bring deep data modeling expertise across multiple paradigms and know how to apply the right approach depending on the context
Have experience leading teams with diverse skill sets across different geographies
Are proficient in the modern data stack, including cloud platforms (AWS, GCP, Azure), as well as data lakes and data warehouses such as Snowflake or BigQuery, and understand how tooling is evolving to support AI use cases

The form of contract of your choosing
Remote work & flexible working hours
Paid sick leave
Paid holidays
Private medical care with dentists & orthodontists package for you and your family
Group life insurance
Psychotherapists support — free online sessions with psychologists and psychotherapists
Home physiotherapy
Multisport card & meditation apps reimbursed 50%
Free access to private language lessons
6 Personal Development Days & 4 Voluntary Days Off
Cafeteria platform — extra “stówka” every month to spend on whatever you want to
Nanny services for parents
Concierge services – a personal assistant to help you deal with your everyday matters
Chill room with table football & PlayStation 5
Free snacks, and ice cream in the office (every day, all year round!)
Free Friday Lunch in the office
Team building events — we party together several times a year during the annual Offsite & Christmas Parties

Director, Data Platform Engineering

Key skills