Analytics Engineer at Swoon | Remote Jobs

Snowflake, Airflow, Kleene, DBT and Sigma. We’re looking for an analytics engineer to own that stack end-to-end: how pipelines get built and maintained, how AI is used within them, how analysis reaches the exec team, and how the wider business self-serves answers. What we’re looking for: This is a single-owner technical role. You will own the warehouse, the transformation layer, the orchestration and the analytics surface the business consumes, and you will shape how they evolve. No data team above you to escalate design decisions to. You will partner closely with the commercial, marketing, and operations leads to turn their questions into insight that is actually executable. That autonomy is the point. You need to be highly self-motivated, comfortable making architecture calls on your own judgement, and willing to fix problems rather than route them. Key Responsibilities 1. Own the data stack Warehouse & modelling: Own the ELT process end-to-end - modelling, testing, documentation, cost and performance management. Orchestration: Own orchestration and ensure pipelines are reliable, timely, and accurate. Source integration: Maintain and extend extraction and loading from any new source. Data quality: Build the tests and checks that mean decisions aren’t made on broken numbers. 2. Own the analytics stack BI layer strategy: Own the decision on how Swoon delivers analytics. Assess whether our current BI layer is the right long-term solution. You will be expected to recommend Swoon’s BI future with evidence and own the consequences. Self-service: Further improve our self-serve analytics for our non-technical colleagues across commercial, operations and marketing to get answers without routing every question through you. 3. Drive AI adoption AI in the data workflow: Use AI tooling to compress the cost of analysis, transformation development, documentation and QA. Review the current standard and where it can’t be trusted. AI enablement across the business: Work with function leads to identify where AI removes manual work - ops reconciliation, customer service triage, content generation, supplier admin - and build or specify the tooling. You are the technical enabler. Track record: Demonstrable experience building and running a production analytics stack. Strong SQL and Python skills, plus Snowflake and orchestration (Airflow or equivalent). AI fluency: Hands-on experience using AI tools in a real workflow. Self-direction: You set your own roadmap, prioritise against commercial impact, and deliver without supervision. Communication: You can explain a technical constraint to a non-technical stakeholder and push back on a bad request without damaging the relationship. Compensation Competitive salary Share options programme Profit share scheme Wellbeing allowance Generous pension scheme Private medical cover for you and your family Holidays, working environment and other perks 27 days holiday rising to 30 with tenure Four months of summer hours finishing at 1 PM on a Friday Free furniture on each anniversary of employment Friends & family discount of 20% Fully remote working Frequent meet-ups, in-person workshops and socials

Analytics Engineer

About this role

Posting details