Senior Event Data Analyst

Groupon is a marketplace where customers discover new experiences and services everyday and local businesses thrive. To date we have worked with over a million merchant partners worldwide, connecting over 16 million customers with deals across various categories. In a world often dominated by e-commerce giants, we stand out as one of the few platforms uniquely committed to helping local businesses succeed on a performance basis. Groupon is on a radical journey to transform our business with relentless pursuit of results. Even with thousands of employees spread across multiple continents, we still maintain a culture that inspires innovation, rewards risk-taking and celebrates success. The impact here can be immediate due to our scale and the speed of our transformation. We're a "best of both worlds" kind of company. We're big enough to have the resources and scale, but small enough that a single person has a surprising amount of autonomy and can make a meaningful impact. About the Role We’re hiring a Senior Event Data Analyst to improve the quality, consistency, and reliability of Groupon’s clickstream and event data. This data powers analytics, experimentation, attribution, and product decisions. You’ll audit existing event flows, find and fix issues, update our canonical schemas, and refresh data quality rules so downstream teams can trust what they see. This role is hands‑on, investigative, and highly cross‑functional. You’ll work closely with engineering, product analytics, and platform teams to trace issues across the entire event lifecycle and resolve them quickly. An AI‑first mindset is expected to accelerate debugging and rule validation. Location: Remote from LATAM Key Responsibilities Event Quality Audits & Semantic Validation Investigate and resolve tracking issues by validating correctness, completeness, and consistency of raw versus canonicalized events. Identify mismatches in naming, attributes, and platform parity against product/UI behavior. Canonical Schema & Mapping Governance Maintain canonical schemas and mapping rules for source‑to‑canonical event transformation. Ensure multi‑source event consistency and collaborate with engineering to correct upstream defects or breaking changes. Data Quality Rules & Alerting Review, simplify, and build clear data quality rules with appropriate severity levels. Reduce alert fatigue while improving real‑issue detection, updating rules as product and upstream systems evolve. End‑to‑End Debugging Trace and pinpoint root causes across front‑end instrumentation, upstream services, canonicalization, pipelines, and downstream consumers. Produce clear RCA documentation and drive cross‑team resolution. Collaboration & Stakeholder Support Lead issue triage meetings with engineering and analytics. Validate funnel definitions, product measurement logic, and provide guidance on measurement hygiene and instrumentation quality. AI‑First Workflows Leverage LLM‑based tools to accelerate investigations, rule reviews, and schema audits. Provide structured feedback to improve internal agent workflows. Key Requirements Core Skills: Proficiency in SQL, Python, event debugging, and analytical problem‑solving. Experience with e‑commerce clickstream data, behavioral tracking, and purchase funnels. Knowledge of event semantics, canonical schemas, and mapping layers. Technical Expertise: Strong understanding of event‑based systems, experimentation, streaming pipelines, and ability to investigate issues across multiple systems and teams. AI‑first mindset with hands‑on use of LLM tools for debugging and analysis. Soft Skills & Work Style: Strong ownership, structured thinking, and ability to operate with minimal direction. Clear communication across technical and non‑technical stakeholders. Proactive, bias toward action, and comfortable with ambiguous data problems. Nice to Have Experience with GA, Adobe Analytics, PostHog, or similar platforms. Background in designing data quality rules, anomaly detection frameworks, or agentic workflows. Familiarity with GDPR or enterprise data governance standards. What Success Looks Like Tracking issues are identified and resolved faster with clear documentation. Canonical schemas remain stable and predictable for downstream users. Data quality rules become simpler, more accurate, and less noisy. Stakeholders confidently use event data for experimentation and product decisions. AI tools meaningfully reduce investigation and debugging turnaround times. Groupon is an AI‑First Company We’re committed to building smarter, faster, and more innovative ways of working—and AI plays a key role in how we get there. We encourage candidates to leverage AI tools during the hiring process where it adds value, and we’re always keen to hear how technology improves the way you work. If you’re passionate about AI or curious to explore how it can elevate your role—you’ll be right at home here. Beware of Recruitment Fraud: Groupon follows a merit‑based recruitment process without charging job seekers any fees. We've noticed an increase in recruitment fraud, including fake job postings and fraudulent interviews and job offers aimed at stealing personal information or money. Be cautious of individuals falsely representing Groupon's Talent Acquisition team with fake job offers. If you encounter any suspicious job offers or interview calls demanding money, recognize these as scams. Groupon is not responsible for losses from such dealings. For legitimate job openings (and a sneak peek into life at Groupon), always check our official career website at Groupon Careers. #J-18808-Ljbffr