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NALA is a fintech company building cross-border payments infrastructure for the next billion users. Since 2022, the company has grown 120x, scaled from 9 to 150+ employees, raised $50M+ from top-tier investors, and was named to the Forbes Fintech 50 in 2025 and 2026. NALA operates two core products: a consumer app enabling cheaper, faster, and more reliable cross-border payments from the UK, US, and EU to Africa and Asia, and Rafiki, a B2B payments infrastructure powering global giants like MoneyGram and Western Union.
As Senior Analytics Engineer, you will own a set of domains in NALA's transformation layer (dbt and Snowflake) and make them genuinely dependable, well-modeled, tested, documented, and semantically rich enough that both humans and AI agents can get trustworthy answers without human interpretation. You will work alongside the existing Analytics Engineer to set the modeling standard the rest of the team builds against.
Key responsibilities include: owning end-to-end modeling and transformation of your domains in dbt and Snowflake; setting and defending modeling methodology, grain, dimensional patterns, and exceptions; making models agent-ready with semantic richness, consistent naming, and business-term descriptions; owning streaming and near-real-time pipelines (Kafka or similar) alongside batch transformation; establishing and enforcing coding standards, systematic testing, and documentation as CI-enforced defaults; optimizing warehouse performance and cost; deploying and supervising autonomous agents against the data stack; and mentoring analysts on analytics-engineering best practices.
Must-have requirements: 3+ years of production dbt experience solving real business problems with demonstrated judgment; a considered position on modeling methodology (grain, facts, dimensions, fan-out, double counting); practical understanding of what makes models trustworthy for AI agents to query; daily use of AI-native tools (Cursor, Windsurf, Claude Code) plus hands-on experience building and maintaining agentic systems; and ownership experience with streaming or near-real-time pipeline infrastructure (Kafka or similar).
