Senior Freelance Analytics Engineer

We’re looking for a freelance Analytics Engineer to join our Data team full-time for 3 to 6 months, bridging the transition between our current Analytics Engineer and their successor.

Swan is a fintech offering embedded banking: companies use Swan to build accounts, cards and payments into their own products. Our Data team, led by Romain, our VP Data, serves the Risk department and our data analysts with the data they need to run and steer the business. Our models also feed reporting to financial regulators, so accuracy, testing and traceability are non-negotiable.

Our Analytics Engineer owns two scopes: business marts on Swan’s core product, such as payments and onboarding, and our Regulatory Reporting models, build and run. During this transition, we need an experienced pair of hands to keep both running and keep delivering.

✨ Your mission

Your goal: deliver reliable, well-modelled data across two scopes of equal weight, business marts for our product and tech teams and our regulatory reporting, then hand everything over cleanly to our next Analytics Engineer.

Your scope:

• Business marts: own the modelling of Swan’s core product domains, including payments and onboarding, and build the marts product, tech and business teams rely on

• Regulatory Reporting: take over the existing models, keep them running, and evolve them as requirements change. Here, modelling excellence is the job itself: every model tested and documented, every figure accurate, and full consistency across regulatory reports

• Handover, twice: ramp up quickly with the outgoing Analytics Engineer, then transfer the full scope to their successor with up-to-date documentation

What you’ll do:

• Design, build and maintain marts for payments, onboarding and other core domains, working closely with product and tech teams

• Run the Regulatory Reporting models day to day: monitor runs, fix failures, make sure reports go out accurate and on time

• Evolve regulatory models as requirements change, without breaking what already reports correctly

• Guarantee consistency: the same figure must reconcile across every regulatory report, with the business marts and with source systems

• Hold a high modelling bar everywhere: clear grain, explicit keys, tests on every model, and documentation that analysts, auditors and regulators can follow

• Work daily with the Data team, software engineers, compliance and business stakeholders

• Keep documentation current throughout, so the handover to the next Analytics Engineer is seamless