Senior Data Analyst - Business Insights & Operations

Job description

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. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1 This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Analyst - Business Insights & Operations based in United States. This is a high-impact analytics role focused on creating a trusted, company-wide source of business intelligence. You will connect data across finance, revenue, product, customer success, operations, engineering, and leadership to enable faster and more informed decisions. The role combines hands-on analytics, data modeling, reporting automation, and strategic business partnership. You will build dashboards, pipelines, metric definitions, and analytical frameworks that make complex business performance easier to understand and act upon. AI-powered tools and agents will be an important part of the role, helping automate recurring analysis and enable self-service insights. Working closely with Data Engineering and senior leaders, you will have significant autonomy to improve how data is collected, interpreted, and used across the organization.