About the role
- Develop a strong understanding of business processes, product workflows, customer journeys, and stakeholder objectives.
- Translate business questions into analytical frameworks, metrics, and clear recommendations.
- Write, optimise, and validate complex SQL queries across large and varied datasets.
- Use Python to automate data preparation, validation, analysis, monitoring, and recurring reporting.
- Identify trends, anomalies, risks, opportunities, and leading indicators that stakeholders should act on.
- Define meaningful KPIs and distinguish decision-useful signals from noise.
- Build intuitive dashboards that explain what happened, why it happened, and what users should do next.
- Use AI tools to accelerate analysis, query development, research, documentation, and workflow automation.
- Partner with Product, Engineering, AI, Operations, Growth, and leadership teams to support data-driven decisions.
- 3–4 years of experience in data analytics, business intelligence, product analytics, or a related role.
- Strong SQL skills, including joins, CTEs, window functions, aggregations, query optimisation, and data validation.
- Strong Python skills, including Pandas, NumPy, APIs, automation, and data transformation.
- Experience building dashboards using Power BI, Amazon QuickSight, Tableau, or a similar BI platform.
- Excellent logical reasoning and the ability to understand and accurately represent complex business rules.
- Ability to communicate insights clearly to both technical and non-technical stakeholders.
- High ownership, intellectual curiosity, attention to detail, and comfort working through ambiguity.
- Exposure to AI/ML, LLMs, AI agents, or modern AI-enabled analytical workflows.
- Experience with AWS data services such as Redshift, S3, or Glue.
- Experience in SaaS, FinTech, payments, tax, compliance, or regulatory technology.