Data Engineer
Data Product Architect
Krakow
Apply on the employer's siteRole description
At Schibsted & Vend Polska we create technology that empowers trusted media and successful marketplaces
As a joint venture between Schibsted and Vend, we develop intelligent, user-focused digital platforms — from news websites and classifieds apps to personalization and AI tools. With 12+ years of experience and teams in Kraków and Gdańsk, we co-create products used daily by millions.
What sets us apart? A culture of trust.
We believe great work happens when people feel trusted and empowered. You’re seen, heard, and valued — not just for what you do, but for who you are. We work in a space of openness, respect, and real recognition, where flexibility is the norm and growth is truly personal.
THE OPPORTUNITY IN A NUTSHELL
You?
A data product thinker who can connect business needs, domain knowledge and technical architecture into data products that people can actually find, understand, trust and use.
Role?
Data Product Architect - a senior role focused on designing how data products should be defined, owned, documented, governed, discovered and evolved across Vend’s product ecosystem.
Tech stack?
Data Mesh, data product design, data contracts, event-driven architecture, Kafka, CDC, schema management, data catalogs, quality frameworks, observability, GCP/BigQuery or Snowflake.
Company?
Vend, home of FINN, Blocket, Tori, Oikotie, DBA and Bilbasen - marketplaces used by millions of people across the Nordics.
Location?
Kraków, hybrid.
Why us?
You will help shape how data becomes a product across a complex marketplace organization. This is a chance to move teams beyond “we produce data” toward “we own reliable data products that create value for known consumers”.
WHO ARE YOU?
You believe that great data products are designed, not accidentally produced.
You understand that data only becomes valuable when someone can discover it, understand it, trust it, use it and rely on it over time. Pipelines matter, but so do ownership, purpose, documentation, quality expectations, consumer needs and lifecycle decisions.
You have strong experience in data architecture, data engineering, data platforms or data product management. You do not need to be the deepest Kafka expert in the room, but you need enough technical depth to make good architectural decisions and challenge weak designs.
You are comfortable working with Data Mesh principles, domain ownership, event-driven data flows, data contracts, schema management, quality frameworks, observability and cloud data platforms.
You can translate business and product goals into data product requirements.
You ask questions such as: Who owns this data? Who consumes it? What decision or product experience does it enable? What quality level is required? What should be documented? What happens when the schema changes? How will consumers know whether they can trust it?
You are strong at structuring ambiguity. When different teams have different expectations, you can create a shared model, define clear responsibilities and help people move from vague intent to practical design.
You communicate clearly in English and can work comfortably with product managers, engineers, analysts, data scientists, platform teams and leadership stakeholders.
WHAT’S THE JOB LIKE?
As a
Data Product Architect
, your mission is to shape the design, usability and adoption of data products across Vend.
You will work at the intersection of product, architecture, engineering and data strategy. Your focus will not be only on how data moves, but on why the data product exists, who it serves, how it should be owned, how it should be discovered, and how it should evolve.
You will help product teams define their data products before they are built or published. This means clarifying consumers, use cases, domain boundaries, ownership, interfaces, quality expectations, documentation standards and lifecycle rules.
You will also help Vend create repeatable patterns for data product design, so teams do not need to reinvent the same decisions every time.
What You Will Work On
Data product design
Help teams define data products with a clear purpose, consumer group, ownership model, interface, quality expectation and lifecycle plan.
Domain and ownership modeling
Clarify which teams own which data, where domain boundaries sit, and how data products should be grouped, named and exposed.
Consumer-centric Requirements
Translate analytical, operational, AI, experimentation and product needs into practical data product requirements.
Data contracts and product interfaces
Define how producers and consumers should agree on schemas, semantics, quality thresholds, compatibility and change management.
Cataloging and discoverability
Ensure that data products are easy to find, understand and evaluate by downstream consumers.
Data product portfolio thinking
Help prioritize which data products matter most, where gaps exist, and how data product coverage should evolve across product areas.
Governance that helps delivery
Create lightweight standards, templates and decision frameworks that make data products easier to build and maintain - not slower.
YOUR TYPICAL WEEK
You might facilitate a data product design session with a product team, helping them define the consumers, business purpose, ownership and contract for a new data product.
You could review a proposed domain model, challenge whether a data product is too broad or too narrow, or help teams decide how to handle overlapping ownership between verticals.
You may work with platform teams on cataloging standards, with product managers on data product roadmaps, with analysts on consumer needs, or with engineers on translating product requirements into technical interfaces.
You may also create templates, maturity models, playbooks and examples that help teams design data products consistently across Vend.
COLLABORATION & STAKEHOLDERS
You will work with product managers, engineering teams, data engineers, analysts, data scientists, platform teams, architects and leadership stakeholders.
You will often act as a bridge between strategy and implementation. Leadership may look to you for clarity on what “good data products” should look like. Teams may look to you for practical guidance on how to define, document and evolve them.
Your influence will come from your ability to make complex data product decisions understandable, structured and actionable.
What Success Looks Like
After 6 months
Priority data products in your area have clearer ownership, consumer definitions, documentation, quality expectations and lifecycle plans. Teams have a more consistent way to describe and design data products.
After 1 year
Vend has a more coherent data product portfolio. Data consumers can find and understand the products they need. Product teams know what they own and how to evolve their data products responsibly. Data product design has become a repeatable practice rather than a one-off effort.
What This Role Is Not
This is
not a pure hands-on pipeline delivery role
. You may go deep technically, but your main focus is productizing data, not personally building every data flow.
This is
not a dashboarding or reporting role
. You will focus on the data products that enable analytics, AI, experimentation and operational use cases.
This is
not a governance-only role
. You will not write standards from the side and disappear. You will work with teams to make better data product design practical.
This is
not an enterprise architecture role detached from delivery
. You will stay close to teams, use cases and adoption.
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