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 stakeholdersTranslate ambiguous business questions into clear analytical problems, delivering actionable insights that drive decision-makingBuild, maintain, and govern trusted metrics and dashboards in Looker using LookML, ensuring consistent definitions and a reliable single source of truthConduct advanced analyses, including funnel diagnostics, cohort analysis, segmentation, churn and activation analysis, and causal inference, to uncover not just what happened, but whyPartner directly with senior stakeholders to scope requests, prioritize work, communicate findings, and confidently present analytical recommendationsEnsure data quality by validating datasets, reconciling discrepancies, and identifying limitations related to data availability or privacy requirementsContribute to the analytics platform by improving documentation, semantic models, coding standards, and best practices that enable the team to scaleCommunicate insights through concise dashboards, presentations, and documentation tailored to different audiencesTo 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 capacityBackground in fintech or banking is strongly preferredAdvanced SQL with strong understanding of complex datasets and multi-row relationshipsExperience with cloud data warehouses such as BigQuery (preferred), Snowflake, or RedshiftStrong experience building governed BI solutions in Looker/LookML or comparable platforms such as Tableau or Power BIExperience with dbt or similar data transformation frameworksWorking knowledge of Python or R for analysis and automationStrong 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 projectsStrong analytical judgment and methodological rigorExcellent stakeholder management and communication skillsCommitment to data quality, governance, and consistent metric definitionsAbility to work autonomously and own projects from problem definition through delivery