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eComID

Senior Data Engineer

Stockholm, Sweden

Seed · $17M · 42d ago Posted 27d ago

About eComID


eComID is building the Shopping Passport for modern commerce - a shopper context layer that enables brands to understand and personalize every shopper from their very first visit. By combining AI-powered sizing, conversational search and intelligent product discovery, we’re making online shopping smarter, more personal and less wasteful.

Launched in Stockholm in 2024, eComID is already operating at scale, reaching more than 20 million shoppers every month. We recently raised a $17.4 million seed round - the largest in European fashion-tech history and the second-largest globally.

We’re backed by H&M Group, Stadium, leading international VCs and some of Europe’s most successful industry leaders and technology founders, including Helena Helmersson, Sebastian Knutsson, Maria Raga and Alan Mamedi.

Now, we’re bringing together exceptional people with warm hearts to build a world-class fashion-tech company from Stockholm. If you want to solve meaningful problems, move fast and help shape how the world shops, this is the place to do it.

What you will work on

We are looking for a Senior Data Engineer who cares deeply about building reliable data systems and takes pride in the correctness and quality of the data that powers the rest of the company.

This is not a role focused only on moving data from A to B.

You will work closely with our AI and product engineers to shape how data is collected, processed, served, and used across machine learning systems, real-time product experiences, experimentation, and analytics.

You will help design and build the data systems behind eComID products, including:

  • Scalable batch and streaming data pipelines

  • Real-time data infrastructure used by production ML inference

  • Feature pipelines and feature serving for machine learning models

  • Reliable datasets for analytics, experimentation, and business intelligence

  • Data models and infrastructure that support product and engineering teams

  • Systems for processing large volumes of behavioural, transactional, and product data

  • Monitoring, validation, and quality controls to ensure data remains correct and trustworthy

  • Infrastructure that bridges data engineering, machine learning, and backend systems

You will be expected to think beyond individual pipelines and help shape the architecture of our data platform as the company grows.

What we are looking for

We are looking for someone who has strong experience building production data systems and enjoys owning them end to end.

You should have experience with several of the following:

  • Designing and operating scalable batch and streaming systems

  • Python in production environments

  • Data modelling and large-scale data processing

  • Event-driven or streaming architectures

  • Building systems that serve data with low latency

  • Supporting machine learning systems in production

  • Cloud infrastructure, ideally GCP

  • Data warehouses and analytical databases

  • Observability, testing, validation, and data quality

  • Designing systems where correctness and reliability matter

You should also be comfortable working closely with machine learning engineers, backend engineers, and product teams.

We care more about strong fundamentals and judgement than whether you have used our exact stack before.

Our current tech stack

Today our core stack includes:

Languages: Python, Go, TypeScript

Services/libraries: GCP, BigQuery, ClickHouse, PostgreSQL, Redis, Apache Beam, Kubeflow, Feast, PyTorch, Typesense, Milvus, ConnectRPC

We are not attached to technologies for their own sake and are open to introducing better tools where they make sense.

What we value

We are looking for someone who:

  • Takes ownership of the systems they build

  • Cares about correctness, not just whether a pipeline runs

  • Enjoys working close to the product

  • Thinks carefully about data contracts, schemas, consistency, and failure modes

  • Can reason about trade-offs between latency, scale, complexity, and reliability

  • Will question existing architecture and proposing better approaches

  • Prefers simple, robust systems over unnecessary complexity
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What we offer

  • A best-in-class team with warm hearts and no ego. We care deeply about the quality of our work, while staying kind, humble, and easy to work with. The goal is always to build the best product possible, not to win internal arguments.

  • A direct connection to product. You will work with product every day, understand why we are building something, help shape the solution, and own the delivery from idea to production.

  • Real ownership. You will have meaningful influence over the architecture, tools, and engineering decisions behind the systems you build. We expect senior engineers to improve the way we work, not just execute tickets.

  • A seat close to AI. You will work side by side with our AI engineers on the data foundations behind models, inference, experimentation, and new product capabilities.

  • Interesting technical problems with real users behind them. The systems you build will directly affect production products, customer experiences, and how quickly the rest of the company can move.

  • Freedom to choose the right tools. We have a strong existing stack, but no attachment to technology for its own sake. If there is a better way to solve a problem, we want to hear it.

  • High standards without unnecessary process. We care about correctness, thoughtful engineering, and maintainable systems, while keeping teams small, communication direct, and decision-making fast.

  • The chance to shape the next stage of the company. We are still early enough that the systems, principles, and decisions you make now will have a lasting impact on how eComID scales.

Benefits

  • Health allowance: 5,000 SEK wellness allowance per year

  • Office: Work from our office in central Stockholm

  • Office perks: Weekly breakfasts and snacks throughout the day

  • Tech: Your choice of computer, phone, and phone contract

  • Learning & growth: Annual budget for courses, books, and conferences

  • Insurance: Extensive coverage, including private healthcare insurance

  • Pension: Private pension insurance via SPP