Staff Data Engineer

IN A NUTSHELL

You? A deeply technical data engineer who enjoys designing reliable data systems, solving complex architectural problems, and raising the engineering bar for data products used at scale.

Role? Staff Data Engineer — a senior individual contributor role focused on the technical foundations of event-driven data products, data contracts, schema quality, observability, and long-term maintainability.

Tech stack? Kafka, Change Data Capture, event modeling, schema evolution, streaming and batch processing, data contracts, cloud data platforms such as GCP/BigQuery or Snowflake, quality and observability tooling.

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 high-quality data products are engineered across a large marketplace ecosystem. This is a role for someone who wants to go deep into technical decisions, influence architecture across teams, and build patterns that make data reliable, discoverable and safe to consume.

WHAT’S THE JOB LIKE?

As a Staff Data Engineer, your mission is to make Vend’s data products technically strong, reliable and scalable.

You will work close to product engineering teams, data engineers, platform teams and technical leaders to design and improve the data interfaces that power analytics, experimentation, AI, operational insights and product decision-making.

This is a hands-on senior IC role. You will not spend your time building dashboards or managing infrastructure. Instead, you will focus on the engineering quality of data products: how events are modeled, how schemas evolve, how data contracts are defined, how quality is monitored, how breaking changes are avoided, and how consumers can trust what they use.

You will be expected to go deep. Some days that means reviewing Kafka topics and event payloads. Other days it means helping a team redesign a data flow, defining a pattern for schema compatibility, investigating a quality issue, or creating reference implementations that other teams can adopt.

YOUR TYPICAL WEEK

You might start the week reviewing a proposed Kafka event model for a product team and identifying risks around schema evolution or consumer ambiguity.

Later, you could work with platform engineers to clarify a golden path for publishing data products, then pair with engineers on improving observability for a high-impact data flow.

You may spend time documenting a reference pattern for CDC-based data ingestion, reviewing a breaking-change proposal, helping resolve a data quality incident, or mentoring engineers on how to design data contracts that remain useful as products evolve.

COLLABORATION:

You will collaborate primarily with engineers: product engineers, data engineers, platform engineers, architects and peer technical leaders.

You will also work with product managers and data consumers when technical decisions need to be connected to real use cases, but your main value comes from technical depth and engineering judgment.

You will influence without direct authority by providing clarity, setting standards, creating reusable patterns and helping teams make better architectural decisions.

WHAT THIS ROLE IS NOT

This is not a platform operations role. You will not be responsible for running Kafka clusters or maintaining cloud infrastructure.

This is not an analytics engineering role. You will not primarily build dashboards, reports or dbt models.

This is not a people management role. You will lead through technical depth, architectural judgment, mentoring and engineering influence.

This is not an ivory-tower architecture role. You will stay close to real systems, real teams and real implementation trade-offs.

We work in a hybrid way and would like to catch up with you at our office in Kraków 2 days per week. If you’re not the working-from-home kind of person, you are of course welcome in our office every day!