We’re IPRally, a Helsinki-based SaaS company building AI tools that make patent search and analysis faster, smarter, and more reliable. We serve patent professionals and R&D teams with technology designed from the ground up for their real-world workflows.

We’re looking for a (Lead) Data Engineer to take ownership of our data platform and play a central role in shaping how data powers our product and business. In this role, you will design, build, and evolve our data infrastructure, own mission-critical data pipelines, and set the technical direction and best practices for data engineering at IPRally.

Our core data workflow involves large-scale inference with transformer models at the heart of our product, and your work will directly impact model performance, product capabilities, and customer experience. You’ll work closely with product, ML, and engineering teams, influencing decisions from architecture and tooling to roadmap priorities.

You’ll be part of the Data Engineering team and supported by Platform Engineering on cloud and infrastructure matters, giving you the space to focus on building robust, scalable data systems and driving the evolution of our data platform. This is a role with real autonomy, where your expertise and decisions will meaningfully shape how we work with data as the company grows.

What you’ll do

• Own, develop, and evolve our data platform, built on GCP and orchestrated with Dagster, and help define its future architecture and direction

• Act as a technical lead for data engineering, influencing architectural decisions, tooling choices, and best practices as the platform scales

• Design and implement ELT pipelines and data workflows, setting standards for performance, observability, and reliability across the platform

• Build monitoring, data quality checks and lineage visibility so our datasets are trustworthy

• Collaborate closely with cross-functional teams to deliver data solutions that drive product and business outcomes

• Work with open-source tooling, host and manage infrastructure

• Leverage technologies like Dagster, Vespa.ai, GCP, PostgreSQL, Ray Data, Kubernetes and GPUs

What we expect from you

• Proven experience in data engineering: data lakes / lakehouse architectures, ELT pipelines and modern data workflows

• Strong SQL skills and experience with both Python and data infrastructure.

• Familiarity with cloud environments and container/orchestration tools 

• You’ve worked with open-source data infrastructure and know how to choose, run and maintain tools

• You are a doer, collaborative, and ready to tackle challenging problems with good judgment

• You are self-driven and thrive in a smaller team environment where your contributions are visible and influence both your own work and that of your colleagues

• You're eager to understand our domain and make engineering choices with business impact in mind

• Startup or scale-up experience is a plus (you’re comfortable with visible details and less dependency on larger teams)

• You have experience taking ownership of complex data systems and making long-term technical decisions

Why join IPRally

• You can feel your impact in our small, driven company of around 50 people working globally

• Flexible hybrid work from Finland (Helsinki + remote) with focus on trust and results

• Six weeks of paid holiday + learning & development support + stock options

• A role where data and AI matter deeply, i.e. realistic problems, not hype

• A culture rooted in transparency, simplicity and reliability

The recruitment process

We like to keep our process simple and transparent. Here’s what to expect:

1. Introductory call with Talent Acquisition Manager and Head of SW

2. Conversation with ML Infrastructure Lead & Data Engineer/Chief Architect

3. Final call with our CTO

If this role sounds like a good match, send us your CV and cover letter (that tells us how you’ve built or run data infrastructure and why this role interests you) by 5.1.2026. Due to the holiday season, we’ll start reviewing applications and invite suitable candidates for interviews after the application period has ended.