Senior Data Analyst - Business Insights & Operations

Accountabilities

• • Build and maintain unified reporting that connects CRM, accounting, invoicing, operational databases, and other business systems into a consistent source of truth.
  • Replace manual reporting and disconnected exports with reliable, scalable data pipelines and appropriate refresh processes.
  • Establish and document shared definitions for key metrics such as MRR, activation, churn, retention, and customer health.
  • Partner with Data Engineering on data architecture, pipeline reliability, warehouse performance, and reporting quality across Redshift and MongoDB Atlas.
  • Contribute to decisions around BI, analytics, warehouse, ELT/ETL, data catalog, and governance tooling, including evaluating whether existing solutions continue to meet business needs.
  • Extend revenue reporting into shared dashboards, including MRR/ARR movements, revenue by segment and product, collections, billing risk, and reconciliation across bookings, invoiced revenue, and collected revenue.
  • Develop cohort, retention, and revenue analyses that explain the underlying drivers of business performance.
  • Query operational data to build product adoption, activation, engagement, API usage, and feature-performance dashboards for Product and Leadership.
  • Connect product usage patterns with customer retention and expansion to identify meaningful business trends.
  • Develop comprehensive customer health reporting that combines product usage, support activity, and customer sentiment.
  • Identify renewal risks and expansion opportunities and provide actionable insights to Customer Success and Sales teams.
  • Partner with Revenue Operations to connect pipeline, funnel, campaign, attribution, and sales-cycle data with broader business metrics.
  • Own recurring executive business review reporting and support board reporting, OKR tracking, and company-wide performance reviews.
  • Act as a strategic thought partner to functional leaders by translating business questions into meaningful analysis and actionable recommendations.
  • Build AI-enabled reporting solutions, including natural-language query agents that can translate business questions into validated SQL or database queries.
  • Develop automated anomaly detection and alerting for critical metrics and proactively surface unusual trends to relevant stakeholders.
  • Use AI tools to accelerate business review analysis, identify inconsistencies across systems, and extract insights from customer conversations and support data.
  • Package successful AI-driven workflows and analytical automations into reusable internal tools that can scale across teams.
  • Map existing systems and reporting dependencies during the first 90 days and prioritize the highest-value reporting gaps.
  • Establish trusted product usage, customer health, and revenue reporting within the first six months, including launching at least one AI-powered reporting workflow adopted outside the Data function.

  Requirements

  • 5+ years of experience in data analytics, business analytics, analytics engineering, or a comparable cross-functional analytical role.
  • Strong SQL skills and hands-on experience with cloud data warehouses, ideally Amazon Redshift.
  • Experience with BI and visualization platforms such as ThoughtSpot, Looker, Tableau, Mode, Hex, Power BI, or comparable tools.
  • Demonstrated experience using AI tools such as Claude, ChatGPT, or similar technologies to automate analysis, accelerate reporting, or build analytical agents.
  • Experience developing data models or semantic layers that enable multiple teams to work from consistent metrics and definitions.
  • Proven ability to connect, reconcile, and analyze data across disparate systems such as CRM, billing, ERP, product, and support platforms.
  • Strong understanding of data quality, reporting automation, metric governance, and business intelligence processes.
  • Excellent stakeholder management skills, with the ability to collaborate effectively with Engineering, Data Engineering, Finance, Sales, Customer Success, Operations, and executive leadership.
  • Ability to challenge assumptions constructively, clarify ambiguous requests, and translate business questions into practical analytical solutions.
  • Experience querying NoSQL or document databases, particularly MongoDB and its aggregation framework, is preferred.
  • Experience in fintech, SaaS, or usage-based or subscription business models is advantageous.
  • Familiarity with AI coding tools such as Claude Code and sufficient Python and SQL knowledge to review, debug, and validate generated code.
  • Experience partnering with existing Finance and Revenue Operations analytics teams without duplicating their responsibilities.
  • Experience evaluating, selecting, or migrating BI and analytics platforms as an organization scales.
  • Strong analytical thinking, communication, prioritization, and problem-solving abilities.
  • Comfortable working independently in a high-ownership, fast-moving environment where autonomy and strategic judgment are highly valued.