Senior Data Analyst

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.