About this role
Job location: Remote in India About the role: Sun King is looking for a Senior Product Analyst to be the analytical backbone of the CRM product team within Enterprise Products. In this role, you will sit close to the product managers, backend and data engineers, working at the intersection of product analytics and data reliability. You will help the team understand how the product is actually used and where it falls short, and you will be among the first to notice when the numbers behind those judgements cannot be trusted. The role will suit someone with technical depth who prefers to collaborate and work closely to a product and its users, is comfortable operating within an established data platform but can also do analysis from new data sources. Document the business rules our systems are supposed to obey, turn them into automated checks that catch contradictions across services, run the exception dashboard that keeps every open break visible and ageing, and extend the catalogue to each new system we integrate or new functionalities we build. Unstructured investigative querying across the warehouse, read replicas, Prometheus metrics and product events — spot-checking against source, sanity-checking new data, and chasing numbers that look wrong. Diagnose the reported data issues by starting from a symptom, checking in the CRM, querying read replicas, Grafana logs, CDC topics and work out whether the pipeline or the application caused it. Bring together data from new sources yourself and run one-time analysis in Python and Redshift, handing over persistent pipelines to data engineering. Build the CRM's business and product dashboards. Work from canonical warehouse tables and the company's standard metric and dimension definitions, helping define what each means for the CRM. Build the CRM's view of system reliability. Write PromQL against the metrics infrastructure already exposes and build product-facing reliability dashboards on top of them — you won't provision new instrumentation, but you will raise the gaps where a metric is missing. Set up alerts for business metrics crossing thresholds, perform checks on the metrics that matter after every release. Build a shared taxonomy for issues raised through various channels and perform analytics on them. Quantify the impact of issues, downtimes - to help the team understand the impact of issues and downtime, including customers affected and potential financial impact. Conduct usage, funnel, and cohort analysis; understand feature adoption through application data and Firebase; design and analyse A/B tests; whether a change actually worked, and making sure the app's events fire correctly and mean what we think they mean.