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IS THIS YOU?
Is owning a big system full of pipelines, bots and AI agents the next step in your growth trajectory?
Have you ever traced a wrong number back to its source, then rebuilt the pipeline so it could never happen again?
When someone quotes a number that feels too big or too small, are you already in the raw data checking it?
Then you know the feeling. You’ve always been the one who builds systems that hold up, and that’s exactly why false data rarely fools you. At Myner, the whole business runs on your work (no pressure): the data that drives growth for brands has to be clean and trustworthy, and you’re the one who makes sure it is.
ABOUT MYNER
Stop waiting. Start growing.
Myner is building the world’s first global consumer omni-panel: a unified, always-on stream of what people buy, consume, watch and think. Myner transforms that data into the fuel that powers our Agentic Flywheels for consumer brands — always-on, continuous loops that both create and validate new product concepts, marketing campaign ideas and more.
THE DATA FACTORY
The Myner app mines the gold from receipts and surveys, and our scrapers haul in mountains of golden data too. The Data Factory refines it all into gold bars. It cleans, processes, matches and weights raw data, so the rest of the company and our partners can build on it with confidence. You own the refinery, and you keep it running, accurate and trustworthy as we grow.
THE ROLE
Own the data refinery.
You own the refinement of Myner's raw data into trusted data products, and lead part of the engineering team that builds it, working closely with our CTO.
WHAT YOU WILL OWN
Receipt extraction: turn receipt images and messy text into structured data, and measure and benchmark how accurate it really is.
Product matching: match every possible item on a receipt to a real product, brand and category, and enrich it with external data, including data we collect by scraping.
Weighting and projection: turn our panel data into numbers that represent the market through weighting, balancing and projection. This is one of the most important parts of the job.
Fraud and quality: develop methods that detect fraud and low-quality data, and feed them back to the Myner app and customer support, so they can act on it, ideally automatically.
AI-first pipelines: build transformations that are fast to change and easy to verify, with AI doing most of the heavy lifting.
Moving data where it's needed: get data out of our app database and into the systems that refine and analyze it.
Shape the stack: nothing is set in stone. You'll choose the technology together with the CTO and the team, and your voice will carry a lot of weight.
WHAT YOU BRING
Builder: you have built, designed and maintained real production data systems yourself, as an early-stage CTO, tech lead or architect, and you have something to show us.
Leader: you have led engineers, and you enjoy shaping both the architecture and the team that builds it.
AI-first: most of the code you shipped in the last three-six months was written with AI, and you have built AI into production systems, not just prototypes.
Data-first: you think in data quality, accuracy and evidence, and you don't trust a number until you know where it came from.
Good judgment and taste: you make sound decisions, care how things look and feel, and are highly regarded by others for these talents.
Cross-functional mindset: you work across teams naturally and never build walls around your own area.
English: near-native is the level we're looking for, where you can express yourself clearly without difficulty.
Self-managed: you plan your own time, make commitments and meet your own deadlines.
OUR STACK
Source data: Supabase (Postgres), with change data capture into the analytics layer, for example PeerDB, Estuary, Airbyte or AWS DMS
Receipt extraction: multimodal LLMs such as Claude or Gemini with structured output, AWS Textract as OCR fallback, and evaluation sets for accuracy benchmarking
Product matching: embeddings and vector search such as pgvector, LLM-assisted matching, and scraping for external product data
Transformations: SQL-based and AI-first, for example dbt or SQLMesh, with DuckDB for fast local iteration
Weighting and projection: Python with Polars, and survey weighting methods such as raking
Fraud detection: rules and models on panel data, wired back into the Myner app and customer support tooling
Infrastructure: AWS, managed with Terraform
NOT A FIT
Big data for its own sake: you prefer large-scale infrastructure to getting the data right. Our challenge is accuracy, not yet volume.
No hands-on building: you've designed systems but haven't built and maintained them yourself.
No AI experience: you haven't built software or data pipelines with AI yet. Working with AI is basic knowledge in this company.
Department walls: you prefer owning your own area over working across teams. Here, the app, the data, support and engineering all connect.
Pace: you prefer the rhythm of a large enterprise. We are a startup that tries things quickly and iterates a lot.
Change: you get frustrated when plans change. We learn as we go, so some work stays and some goes straight into the bin.
TEAMWORK
Remote, together: we work remotely, meet weekly or on demand, and meet in person once a month.
Small team, big leverage: a 3–5 person engineering team with loads of AI harnesses that keep evolving.
Delivery over hours: we care about what you ship, not when you work on it.
Our primary working hours follow Central European Time.
HOW WE HIRE
4 steps. 3 hours. 2 weeks.
Our process is crisp and concise, built to give you a clear answer fast.
Informational Interview 30 MIN
A direct conversation about the role, the team and what you're looking for. Bring your questions.Online Assessment 30 MIN
A brief skill and personality assessment that helps us evaluate your fit and guides our next interview.Team Interview 90 MIN
Work through real problems with the people you will build alongside.Founder Finale 30 MIN
Meet the founder & CEO. Talk ambition, ownership, culture and Myner's future.
Great candidates complete the entire process within 2 weeks of submitting their resume.
READY TO FLY?