Senior Data Analyst

About The Role

Rain is building a modern data team from the ground up. This role is for a high agency individual who ensures data is useful and adopted, not just available. You’ll own the tools and data that all of our leaders and teams rely on: dashboards, weekly insight loops, and deep dives that turn messy signals (logs, events, operational workflows, partner escalations) into clear priorities and actions.

You’ll also be a key driver of metric correctness and adoption: reconciling definitions, running acceptance tests, and closing instrumentation gaps so teams can self-serve.

What You’ll Do

• Build dashboards, metrics, and data products that enable self-serve analytics, providing clear and trusted insights that drive operational and product decisions.
• Establish a proactive insights cadence, surfacing opportunities, risks, and trends before stakeholders have to ask.
• Partner with Product, Engineering, and Operations to define, measure, and improve the metrics that matter most.
• Own data quality and metric governance, ensuring key business questions can be answered accurately and reliably.
• Design and analyze experiments, helping teams evaluate product changes and make data-informed decisions.
• Perform user segmentation, cohort analysis, and behavioral analysis to uncover opportunities for growth, engagement, and retention.
• Translate ambiguous business questions into analytical frameworks, actionable recommendations, and measurable outcomes.

Requirements

• A structured approach to problem solving and the ability to turn ambiguous questions into clear analyses, actionable insights, and recommendations.
• A strong bias for action and comfort owning end-to-end analytical work, from problem framing and data extraction to insight generation and execution support.
• Excellent communication skills and experience acting as a trusted thought partner to both technical and non-technical stakeholders.
• Advanced SQL expertise, including complex joins, query optimization, data modeling concepts, and working with imperfect or evolving datasets.
• Strong experience with BI and analytics tools such as Metabase, Mode, Lightdash, Hex, Looker, or similar platforms.
• Experience designing intuitive dashboards and self-service reporting solutions.
• Familiarity with experimentation frameworks, A/B testing, cohort analysis, and performance measurement.
• 3–5+ years of experience in data analytics, product analytics, business analytics, data science, consulting, or related analytical roles.

Bonus Attributes

• Experience in fintech, payments, card programs, banking infrastructure, or related domains.
• Proficiency in Python for analytics and automation (pandas, notebooks, scripting, lightweight pipelines).
• Experience with dbt and analytics engineering best practices.
• Familiarity with modern data stack technologies and concepts.
• Experience working with customer segmentation, clustering techniques, or predictive analytics.