Senior Data Engineer

About Vatix

Vatix is a fast-growing SaaS company founded in London and Kraków in 2019. We're on a mission to bring a fresh, user-centric approach to the world of Governance, Risk, and Compliance software, with a particular focus on Health & Safety and Operational Excellence. Today, over 800 businesses and government organisations around the world trust our platform to protect their people, streamline safety workflows, and drive operational performance.

We're not VC-owned, and we're not chasing vanity metrics. Instead, we're building a long-term, sustainable company focused on solving real-world problems. Our customers include industry leaders such as Cambridge University, Siemens, Intel, and major government departments, organisations that depend on us for mission-critical systems.

At Vatix, you'll work across a diverse product suite spanning web applications, mobile apps, IoT-enabled safety devices, and data platforms. That means an opportunity to grow across a range of technologies, supported by a team that values quality, simplicity, and mentorship.

The Role

Contract: B2B Level: Senior

We're looking for a hands-on Senior Data Engineer who gets things done and brings ownership to how we do them. This is first and foremost a building role. Most days you'll be close to the work: designing the data models, shaping the pipelines, and owning the warehouse and the datasets behind our dashboards. The "lead" part is the ownership that comes with it: you own the technical data backlog and plan where the work goes. You set the direction for how data moves through Vatix, then build it.

Our data capability has grown quickly alongside the product, and we're now at the point where someone needs to own it deliberately: bring a proactive plan, decide where we invest and why, and get involved early in product and architecture decisions rather than after they're built. When we rebuild a major product area, you're the person asking what the right data model and storage approach actually is, before the build starts, rather than fitting analytics around it afterwards.

A lot of data work in any growing company starts out manual and reactive. A big part of this role is moving us the other way: spotting where well-designed systems remove repetitive work, and building them. For example, rethinking how we manage our analytics datasets in the backend so that provisioning a new customer's dashboards during onboarding becomes automated rather than hand-cranked. We want someone who sees those opportunities and acts on them.

Our data warehouse already replicates production data into Redshift in near real time and feeds the embedded dashboards our customers use. Your job is to own that platform, make it more reliable and capable as we grow, and turn data into a genuine product advantage.

Like the rest of our engineering, our SDLC is heavily AI-enabled. You'll use AI to accelerate the work, but you are the guardrail: you decide whether a model is correct, a pipeline is sound, and the numbers in a customer's dashboard are ones they can trust.

How We Work

• Design before implementation, always
• Continuous integration & quality assurance before shipping
• Small, frequent releases over big, risky ones
• Scrum, retrospectives, and room for improvement
• Hybrid: 2 days per week in our Kraków office, with flexibility on the remaining days
• AI tools encouraged and supported as part of our workflow

What We Offer

• B2B contract
• Hybrid work culture (2 days in Kraków office)
• A fast-paced, supportive environment focused on learning and mentorship
• Training budget and regular growth check-ins
• Access to modern tooling, including AI assistants
• Regular team meetups and collaboration sessions
• Holiday entitlement aligned with Kodeks Pracy (Labour Code)
• Office Location: Józefitów 8, Kraków

If you're excited by the idea of joining a company with serious ambition, a clear roadmap, and a strong focus on people, this is the place to build your career.

Technical Skills:

• Strong SQL and hands-on experience with modern cloud data warehouses (Redshift, BigQuery, Snowflake, or similar).
• Solid grasp of ETL/ELT, CDC, and data pipeline design, and the judgement to know when a managed service beats custom code.
• Strong relational data modelling, and the ability to reason about performance, cost, and scale.
• Python for scripting, automation, and data work.
• Comfort with JSON, structured and semi-structured schemas, and querying APIs.
• Experience building data products or dashboards for internal or external users.

Ownership and Planning:

• A track record of owning data work end to end and driving it to done, not just contributing to it.
• Comfortable planning a backlog and shaping technical decisions early, not just executing work someone else has scoped.
• Sound judgement about trade-offs: when something is good enough to ship, when it isn't, and where correctness is non-negotiable.
• Genuine ownership: you stand behind what you ship and fix it when it breaks.

Mindset:

• Openness to an AI-enabled SDLC, treating AI as a tool you direct and verify, not a replacement for engineering judgement.
• Curiosity about emerging data tooling and how it can improve how the team works.
• Self-starter with high ownership and a collaborative, proactive approach.

Soft Skills:

• Excellent communication in English, able to explain complex data concepts to both technical and non-technical audiences.
• The instinct to ask rather than guess.

Nice to Have:

• Experience in B2B / enterprise SaaS, especially security, compliance, or data-heavy products.
• Experience with embedded analytics or BI tooling.
• Experience with AWS data services (Redshift, Glue, Athena, S3, Lambda) and Infrastructure as Code (Terraform).
• A STEM degree or equivalent practical experience.