Senior Data Analyst

We are looking for Senior Data Analyst who has deep technical analytics with business partnership. In this role you aren't just expected to build dashboards, you're expected to own the entire analytical lifecycle and influence business decisions.

What you'll do:

• Own analytics for one or more business domains (such as Lending, Payments, Risk, Sales, or Growth), acting as the primary analytics partner for stakeholders.
• Translate ambiguous business questions into clear analytical problems, delivering actionable insights that drive decision-making.
• Build, maintain, and govern trusted metrics and dashboards in Looker using LookML, ensuring consistent definitions and a reliable single source of truth.
• Conduct advanced analyses, including funnel diagnostics, cohort analysis, segmentation, churn and activation analysis, and causal inference, to uncover not just what happened, but why.
• Partner directly with senior stakeholders to scope requests, prioritize work, communicate findings, and confidently present analytical recommendations.
• Ensure data quality by validating datasets, reconciling discrepancies, and identifying limitations related to data availability or privacy requirements.
• Contribute to the analytics platform by improving documentation, semantic models, coding standards, and best practices that enable the team to scale.
• Communicate insights through concise dashboards, presentations, and documentation tailored to different audiences.

To succeed in this role, you'll need to have:

• 5+ years of experience in data analytics, including at least 2 years operating independently in a senior individual contributor capacity.
• Background in fintech or banking is strongly preferred.
• Advanced SQL with strong understanding of complex datasets and multi-row relationships.
• Experience with cloud data warehouses such as BigQuery (preferred), Snowflake, or Redshift.
• Strong experience building governed BI solutions in Looker/LookML or comparable platforms such as Tableau or Power BI.
• Experience with dbt or similar data transformation frameworks.
• Working knowledge of Python or R for analysis and automation.
• Strong foundation in statistics, experimentation, and causal analysis (A/B testing, cohort analysis, regression, diff-in-diff, regression discontinuity, etc.).
• Ability to transform ambiguous business questions into well-scoped analytical projects.
• Strong analytical judgment and methodological rigor.
• Excellent stakeholder management and communication skills.
• Commitment to data quality, governance, and consistent metric definitions.
• Ability to work autonomously and own projects from problem definition through delivery.