Senior Data Platform Engineer

Senior Data Platform Engineer

Much Better Adventures books small-group adventure holidays run by local, independent guides in wild places around the world. We're a certified B Corp, on a mission to get more people into the world's wildest places, support the local businesses who protect them, and prove that adventure travel can be a force for good. We're a community and VC-backed scale-up in one of the fastest-growing sectors of travel, and a remote-first team coming together for annual company meet-ups.

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.

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