Job description

Product Analyst Product Analyst Scope: We're a technology solutions company building Hatch, a client-facing IT asset management and visibility platform. We've standardized on Datadog as our telemetry and analytics stack, work AI-first across our tooling, and need someone to define and stand up our product analytics and attribution practice. This role blends product judgment with hands-on technical execution. The challenge is not simply building dashboards; it is defining the right metrics, linking them to provable outcomes, and ensuring the underlying data can support them. We are looking for someone who has done this before and can build alongside our engineering team. What you'll deliver 1. Pod-level metric frameworks — Work with each of our product pods to define their north star and supporting metrics, tied to causal outcomes we can attribute. For each metric: facilitate agreement on the definition, identify the data source, and get it implemented as a durable metric. This is the core of the engagement. 2. Instrumentation gap analysis — Audit our existing Datadog RUM events and tagging against the metrics we need, spec the correct capture, and partner with engineering to ship it. Establish a governance checklist so new features launch instrumented. 3. Attribution model — Design how product usage joins to business outcomes (Salesforce/CPQ: opportunities, renewals, expansion), including the export path from Datadog to a queryable layer. Prove it by answering at least one real go-to-market attribution question end-to-end. 4. Reporting & consumption layer — Partner with leadership to define how teams will consume product metrics, then build the right reporting layer. This may include pod-level dashboards, feature-release views, executive rollups, and monitors for key product metrics. You will shape the right outputs rather than follow a preset list, using Datadog, our internal data platform Unity, or both as appropriate. Product Analyst Skills: Must Have • Proven product analytics judgment in B2B SaaS: you've defined north star metric frameworks for product teams, can distinguish causal outcome metrics from vanity metrics, and have opinions about activation, retention, and adoption, especially in account-based (multi-user-per-customer) products • Experience facilitating metric definition across product, engineering, and leadership, landing on definitions teams actually adopt and act on • Experience connecting product usage to business outcomes (attribution to pipeline, renewals, expansion) • Strong database and data-modeling skills: how events, users, and accounts should be structured, what joins are valid, and when a metric is wrong by construction • Fluency working with AI tools as a core part of your workflow: we build dashboards, queries, and pipelines AI-first; you direct the work, own the model, and catch bad output • Hands-on Datadog experience beyond ops use: RUM, custom metrics, and comfort scripting against the Datadog API Product Analyst Skills: Nice to Have • Strong SQL for validating AI-produced work • Datadog depth: DDSQL, reference tables, cost/cardinality management, and working around the limits of Datadog's product analytics feature set (funnels, cohorts) • Warehouse experience (Snowflake, BigQuery, or Postgres), scheduled exports, orchestration • Ability to ship instrumentation changes yourself (JavaScript/TypeScript, comfort in a modern codebase) #RT #DICEJOBS #MCB

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