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# Senior Data Platform Engineer

- **Company:** Much Better Adventures
- **Location:** London, UK (Remote available)
- **Experience:** Expert
- **Salary:** £63,450.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Google AdWords, Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, BigQuery, Data Infrastructure, Software Debugging, Python (Programming Language), Software Tools, Standard Sql, TypeScript, Datadog, Business Intelligence Development Studio, Snowflake, Data Analytics, Hubspot, Terraform, GPT
- **Published:** August 18, 2026
- **Apply:** https://www.adzuna.co.uk/jobs/details/5846799978

## About the Role

* You care about getting things right. Attribution, commission and revenue numbers get subtle here, and we'd always rather take the time
 * You thrive on the pace of a fast-growing business. Priorities move quickly, and you'd rather help shape a young function than inherit a fixed one
 * Strong multi-tasking and project skills. Working with AI means you can have several models, pipelines and changes in flight at once, and that only pays off if you can keep track of them all, keep them moving, and judge when each one is finished
 * Deeply comfortable working natively with AI. AI tools are part of how we work every day, and we'd love to hear how you already use them - where they help, where they don't, and how you check what comes back. We'd be especially interested if you've chained systems together through MCP, so an assistant like Claude or ChatGPT can work directly against your warehouse, repo and tooling rather than you copying things between them
 * Comfortable working independently in a remote team - organised, self-motivated and good at managing your own priorities

Technical skills

 * Strong SQL and hands-on production experience with a cloud warehouse - Snowflake ideally, though BigQuery or Redshift are fine
 * Solid dbt experience: incremental models, tests, macros, and a view on how a project should be structured as it grows
 * Consistent data instrumentation and collection for web tracking, with hands-on Segment experience. You'd own the event schema behind our clickstream - making sure events, identifiers and campaign parameters are captured the same way across the site, because our attribution, funnel and experiment analysis all depend on it
 * Confident Python. You'll be writing ingestion, orchestration and service code, not just notebooks
 * Experience with a modern orchestrator - Dagster, Airflow, Prefect or similar - including the operational side: retries, backfills, freshness, and the occasional early morning
 * Infrastructure-as-code and cloud fundamentals. AWS with CDK or Terraform is ideal; what matters is that you can deploy and debug your own infrastructure

## Description

We're building something we're genuinely excited about: a small, highly skilled, AI-first data team.

We're growing quickly, and the platform underneath us has had to grow with it. Over the past two years we've built something that stands up against companies many times our size - Snowflake, a rigorously tested dbt project, daily ingestion from around 25 sources, orchestration in Dagster, and infrastructure defined in code on AWS.

This is an unusual opportunity: a modern, well-architected platform with no legacy tax, and full ownership of it from day one. You wouldn't be inheriting someone else's roadmap - you'd be deciding where this goes next.

You'll join as Senior Data Platform Engineer, reporting to the Head of Data & Analytics Engineering. It's a broad role, and that's the appeal. In a given week you might write an incremental dbt model against Snowflake, track down a Dagster asset that quietly stopped landing ad spend, and deploy a Step Function via CDK.

We move quickly, and trust matters enormously in a remote team. We also care a lot about doing things properly - tested models, monitored pipelines, and infrastructure you can reason about.
What You'll Be Doing

 * Owning our Snowflake warehouse and the dbt project on top of it - around 300 models across raw, transformation and warehouse layers, with roughly 1,700 data tests, versioned model contracts and semantic definitions feeding our reporting
 * Looking after the numbers the business runs on: commissions, cancellations, bookings and marketing attribution all live in these models
 * Owning daily ingestion from around 25 sources through dlt and Dagster - Segment, HubSpot, Google Ads and Analytics, Meta, TikTok and the rest - along with the assets, schedules, sensors and freshness checks around them
 * Running our AWS infrastructure, defined in CDK: Step Functions, Lambda, S3, Athena and Iceberg, with lineage and monitoring on top
 * Leading our observability in Datadog - dashboards and monitors defined as code, Snowflake usage and cost visibility, and alerting that surfaces problems before anyone else notices them
 * Keeping it all healthy - picking things up confidently when something does break, and making sure it doesn't happen twice
 * Using AI tools throughout your work - and helping shape how a modern, AI-first data team operates, * dlt, or experience building ingestion from marketing and CRM APIs (they're all badly behaved in their own special ways)
 * BI tooling - we use Hex, and we're moving the last of our reporting off Metabase
 * TypeScript, for the infrastructure side
 * E-commerce or travel industry experience - or marketplace and subscription businesses more broadly


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