Job Opportunities API

👋 About Us NALA is building Payments for the Next Billion. Faster, smarter, and fairer transfers for everyone. Since 2022, we've grown our business 120x, grown the team from 9 to 150+, raised $50M+ from top-tier investors , and were named to the Forbes Fintech 50 in 2025. We operate two core products: • NALA , our consumer app makes cross-border payments cheaper, faster and more reliable for the global diaspora. Allowing users to send money from the UK, US and EU to Africa and Asia. • Rafiki , our B2B payments infrastructure, is powering global payments. Our team includes alumni from Wise, Stripe, Monzo, Revolut, and CashApp — operators who’ve scaled world-class products. We act with urgency, think deeply, and put our customers first always. At NALA, this isn’t just a job. It’s ownership, impact, and the chance to change global payments forever. Join us in building Payments for the Next Billion 🙌 Your Mission As Senior Analytics Engineer, you'll own, uplift and maintain NALA's data transformation layer — the foundation that all reporting, governed metrics, self-serve analytics and AI-powered capabilities depend on. Your work will add semantic richness, structure and governance to NALA's data, ensuring every model is documented, tested and described in a way that both humans and AI agents can interpret and trust. Agentic analytics is arriving fast, and this role exists to help ensure NALA's data foundation is ready for it. 🎯 Your Responsibilities in this Role • Own the transformation layer (dbt + Snowflake) — refactoring, enforcing best practices, and evolving our data stack to a best-in-class standard • Take ownership of streaming data pipelines alongside batch transformation — ensuring real-time and near-real-time data flows are reliable, cost-efficient and well-integrated into the broader data architecture • Establish and enforce coding & agentic coding standards, systematic testing and documentation as CI-enforced defaults across all data models • Optimise warehouse performance and cost efficiency, identifying and resolving the query patterns and materialisation choices driving unnecessary spend • Build the foundation for AI-powered self-serve by ensuring models carry the semantic richness and documentation that agents need to return reliable answers • Scope and resolve orchestration decisions (dbt Cloud vs Dagster) and own the infrastructure roadmap for the transformation layer • Support and mentor analysts on analytics engineering best practices, raising the engineering standard across the team 🔥 Must-have requirements • 4+ years hands-on experience with dbt (ideally fusion) — building, refactoring and maintaining production-grade transformation layers • Strong SQL, Python and data modelling skills with a clear understanding of warehousing and modern data architecture • Snowflake or Databricks experience including query performance tuning and cost optimisation • Deep proficiency with AI-assisted development workflows (Cursor, Windsurf, Claude Code) to force-multiply engineering output and accelerate delivery • Track record of implementing testing, CI/CD, documentation standards and PR review workflows in dbt projects • Comfortable owning an infrastructure roadmap — can assess the current state, propose a plan and execute without being directed step-by-step 💪 Nice to have requirements • Semantic layer experience (Cube, dbt Semantic Layer) and understanding of how governed metric definitions sit on top of a transformation layer • Familiarity with orchestration tools (Dagster, Airflow, dbt Cloud etc) • Experience with Hex or similar modern BI/notebook platforms • Experience in fintech, payments or regulated environments where data accuracy and governance carry real business consequences • Familiarity with experimentation frameworks and product analytics ✅ Success in the role looks like 3-Month Metrics • Full ownership of the transformation layer and warehouse, with a clear understanding of the current architecture, cost drivers and priorities 6-Month Metrics • Full ownership of warehouse coding standards, data architecture and infrastructure • Measurable improvement in the cost and efficiency of supplying data to the business • A clear data infrastructure roadmap delivered for the following 6 months ➡️ Interview Process You will need to first submit your application through our ATS Workable. There is no need to submit a Cover Letter. If successful you will be selected for our interview process which has 4 stages: • [30mins] Interview with the Talent Team • We want to understand your experience and motivations. • [1hr] Live Assessment with the Data Team • A practical exercise based on a realistic task, completed and discussed with a member of the data team. • [1hr] Interview with the Hiring Manager • A deeper dive into your experience, technical depth and approach to the role. • [45mins] Senior Leadership Interview • A final conversation with a member of our senior leadership team to discuss motivations and ask your own questions. ⭐️ Benefits • 27 Days Off Plus UK Bank Holidays : Take the time to decompress. Working at a startup is hard! • Birthday Leave: Celebrate your special day with a bonus day off to take off in that month. • Enhanced Parental Leave: We offer 16 weeks of full pay for the primary caregiver and 4 weeks of full pay for the secondary caregiver (After a 6-month probationary period) • Enhanced Pension : Salary sacrifice pension scheme via Penfold giving you flexibility and control on how you save for your future! • Global Workspace : Get access to WeWork locations worldwide. • Learning Budget : Fuel your growth with $1000 annually for learning and development. • Sarabi : Themed snacks and Friday lunch focused on building great working relationships with the team. • Monthly Socials : Join fun social events every month for great times. • Free Coffee : Enjoy barista-style coffee at your fingertips.