aios - Head of Data at AIOS — Remote, $150k-$300k/yr inc equity

• Stack: You’ll be the DRI for data across every AIOS brand and market, including ingestion, Redshift, dbt, Hex, product-event tracking, integrations, data quality, monitoring, and access. • Architecture: You’ll define how our data platform should evolve as AIOS grows by orders of magnitude. You’ll make the important architectural decisions while working through our Analytics Engineering Lead and the rest of the team to execute them. • dbt: You’ll establish clear standards for staging, intermediate, and marts models. You’ll define how new models are proposed, designed, reviewed, tested, documented, deployed, and eventually deprecated. • Metrics: You’ll own the definitions behind the metrics that run AIOS across growth, activation, retention, revenue, product, clinical operations, CX, and Ops. You’ll eliminate conflicting definitions and turn core metrics into trusted company infrastructure. • Hex AI: You’ll make Hex AI the best possible interface for understanding the business. Leaders should be able to ask important questions against clean, intuitive models without recreating business logic in every dashboard. • Performance & Reliability: You’ll work with the team to keep our warehouse and pipelines fast, reliable, and cost-efficient as data volume and usage grow. You’ll set expectations for performance, freshness, monitoring, incident response, and cost. • Experimentation: You’ll establish how AIOS designs, instruments, and evaluates experiments. You’ll ensure results are statistically sound, prevent teams from drawing confident conclusions from weak evidence, and identify when specialist Data Science support is needed. • Engineering: You’ll partner closely with Engineering on source schemas, product events, breaking changes, data contracts, and backfills. Product changes should flow predictably into trustworthy analytical data. • Business Partner: You’ll become a key partner to every functional lead. You’ll understand their domain deeply, challenge weak KPIs, and help them find the measurements that actually drive better decisions. • Build the Team: You’ll lead our existing data team, hire an additional Data Engineer once you’re onboarded, and continue growing the function based on what the company needs most. • Regulatory Evidence: You’ll start designing the data foundations required to demonstrate the quality, safety, and performance of our clinical and AI systems. When we talk to regulators, we should be fully data-backed. • Vendors: You’ll own our relationships with Hex and other important data vendors. You’ll lead escalations, push for reliable products, evaluate whether tools still serve us, and negotiate as AIOS scales. • Systems: You’ll move important business logic out of ad hoc dashboards and into governed models. When a problem repeats, you’ll turn the solution into reusable scaffolding rather than fixing it for the fifth time. • Experience: You have 5+ years as a hands-on data IC and 3+ years leading teams, including directly managing at least a couple of people. Most of your career has been spent close to the metal. • SQL & dbt: You’re deeply fluent in SQL and dbt. You can read complex transformation logic, identify grain and join problems, review a marts-layer design, and quickly work out why two reports disagree. • Data Architecture: You’ve helped design and operate a modern data platform spanning ingestion, a cloud warehouse, transformation, reporting, and monitoring. You understand how each layer should fit together. • Data Engineering: You understand how production data systems behave beyond the modeling layer. You can reason about orchestration, incremental processing, dependencies, backfills, failure recovery, freshness, and data-quality controls • Data Modelling: You know how to design models that remain clean and understandable as the business changes. You care about contracts, tests, lineage, ownership, documentation, and intuitive interfaces. • Metrics: You can turn an ambiguous business goal into a precise metric. You deeply understand funnels, cohorts, activation, retention, churn, revenue, and growth. • AI-Native: You use AI heavily in your own work and have strong instincts for making AI-assisted analysis more reliable, contextual, and useful. • Judgement: You know which logic belongs in dbt, which belongs in Hex, which requests should become canonical models, and which requests should not be built at all. • Leadership: You set a crisp direction and quality bar while giving strong people room to execute. You know how to develop an existing team while building the broader function around it. • Player-Coach: You’re excited to primarily operate at the managerial and system level, but you haven’t lost the ability or willingness to inspect the actual work. You won’t hide behind your team. • Stakeholders: You challenge senior leaders without hesitation when a KPI is misleading or poorly defined, then work with them to build a measure that drives better decisions. • Reliability: You’ve established monitoring, data-quality checks, ownership, and incident processes for business-critical data. You don’t accept “the dashboard sometimes doesn’t update” as an enduring fact of life. • Ownership: When a model is wrong, a dashboard is stale, or a vendor is failing us, you take responsibility for reaching the outcome. You do not stop at identifying which system or person is technically at fault.