Senior Data Engineer

THE COMPANY:

AtFit Collective, we’re solving one of the fashion industry’s biggest - and most expensive - problems: poor fit. It's the leading cause of returns, responsible for nearly$1 trillion in lost revenue,4 billion pounds of textile waste, and10% of global carbon emissionseach year.

Rather than adjusting sizing after the fact,we prevent bad fit from the start. Using machine learning and generative AI, we simulate and predict how garments will perform on real bodies, eliminating poor fit before a single item is made. It’s a shift from subjective guesswork to data-driven decision-making that reduces returns, cuts waste, boosts conversions, and drives loyalty.

We’re building theFit Operating Systemfor the modern fashion supply chain and we're looking for a talented and experiencedSeniorData Engineerto help power this transformation.

THE ROLE:

As a SeniorData Engineerat Fit Collective, you’ll build the infrastructure that fuels everything from AI-powered predictions to insights delivered directly to our customers. If you love designing clean, scalable pipelines and want to see your work impact both product and planet, this is your kind of challenge.

You’ll join a collaborative, fast-paced team that values curiosity, creativity, and code that works. You’ll shape systems from the ground up, with real ownership and the chance to influence how we grow.

THE PRODUCT:

Fit Collective’s product combines advanced analytics, machine learning, and a low-code interface to deliver powerful insights across the fashion supply chain. Over the next 12 months, we’re launching a Shopify app that automatically updates product fit recommendations and descriptions, powered directly by manufacturing data, helping brands reduce returns and improve their bottom line.

Our Current Stack:

• Data Warehouse and Tools: DBT, Snowflake, Airbyte
• Languages: Python, TypeScript,Node.js, React
• Cloud & Infra: AWS (S3, ECS), Docker
• Orchestration: AWS Lambda and Step Functions
• CI/CD: GitHub Actions
• Analytics Layer: GoodData

What You’ll Work On:

Data Pipelines:Design, build, and maintain robust ETL/ELT pipelines using dbt to transform raw data into reliable, production-grade models, supporting machine learning, analytics, and product features.

Data Modelling & dbt Mastery:Own the full lifecycle of data models in dbt, including:

• Designing scalable fact and dimension tables
• Managing Slowly Changing Dimensions (SCDs) using snapshots or incremental models
• Building and maintaining seeds for reference data
• Writing thorough tests and documentation to enforce data quality and governance

Architecture Ownership:Help shape our dbt folder structure, model contracts, and naming conventions to support long-term maintainability across multi-tenant data products.

Automation & Efficiency:Use orchestration tools like Airbyte, AWS Step Functions, and GitHub Actions to ensure seamless deployment of dbt runs and freshness checks.

Cross-Team Collaboration:Act as the bridge between product, ML, and analytics, ensuring their needs are met through scalable, transparent, and well-documented data models.

Governance & Monitoring:Implement dbt tests, freshness checks, and observability practices to guarantee trust in downstream analytics and ML applications for governance and audits.

What You Bring:

• Experience: 5+ years in data engineering or backend development with a focus on implementing multi-tenant, data-heavy systems, ideally in a startup or fast-moving environment.
• Technical Stack:
• Languages/Tools: Python (REST API integrations), DBT, Airbyte, GitHub Actions
• Modern Data Warehousing: Snowflake, Redshift, Databricks, or  BigQuery. 
• Cloud & Infra: AWS (ECS, S3, Step Functions), Docker (Kubernetes or Fargate a bonus)
• Data Modelling: Strong grasp of transforming structured/unstructured data into usable models (facts, dimensions, metrics). You know when to use snapshots vs incremental, can use seeds for controlled lookup data, and enjoy keeping models modular and maintainable.
• Modelling Expertise:
• Comfortable working acrossnormalizedandanalytics-ready star schemas
• Deep understanding of SCD types, particularly Type 2,using dbt snapshots
• Experience working with multi-tenant datasetsand aligning models across clients/domains
• Strong discipline aroundtesting for freshness, uniqueness, nulls, and relationships,documentation, andcontracts
• Mindset:
• You’re an agile thinker who values delivering value fast over perfection
• You communicate very clearly and are happy to collaborate with others.
• You’re hungry to learn, open to feedback, and excited to grow in a dynamic team
• You’re passionate about problem solving and focus on solutions and outcomes, and don’t crumble under pressure

Overview:

• Location: Remote (Within +- 3 hours UK time)
• Work Style: Hybrid (4 days per month in the office in London)
• Employment Type: Full-Time
• Salary: £70-90K/year depending on experience
• Equityvia employee share option scheme

Why Fit Collective?

You'll play a key role in:

• Revolutionising how fit is defined and delivered
• Reducing waste and emissions at the root
• Helping fashion become more sustainable, efficient, and customer-focused

We’re a close-knit, mission-driven team building something truly impactful, and we’re just getting started. If you care about code quality and climate impact, about automation and innovation, we’d love to have you on the journey!