Data and Analytics Lead

Manifest OS is the leading AI-native company on a mission to replace the billable hour and make legal services more accessible for American businesses and consumers. We power the next generation of AI-native law firms with one unified global brand, a proprietary technology platform, and a centralized back office — enabling lawyers to eliminate the administrative burden and focus on delivering exceptional outcomes for their clients. Manifest OS has raised a $60M Series A from Menlo Ventures, Kleiner Perkins, First Round, and Quiet Capital.

Data & Analytics sits within Strategic Initiatives and supports Manifest’s go-to-market motion: B2C and B2B marketing, sales, RevOps, and finance. The team owns the BigQuery warehouse, the pipelines that feed it (CRM, ad platforms, product, billing), the dbt models on top, and the reporting that stakeholders across the company run on. It’s a small team with company-wide surface area: every growth decision at Manifest, where to spend, which channels work, what a customer is worth, runs through this team’s output.

You will own Manifest’s data foundation end to end for the go to market team and turn it into the single trusted layer every team and AI agent runs on. This is a player-coach role and you’ll be accountable for the function's outcome.

• Own the source of truth: model revenue (Stripe), spend (every ad platform, not just the ones piped in today), and funnel (HubSpot) into one reconciled BigQuery layer, today these live across four reporting surfaces and reconciliation is manual

• Own web and product analytics for growth: reconcile Amplitude with GA4, and stand up AEO reporting as search shifts to AI answer engines

• Build toward conversational BI: the semantic layer, curated datasets, and AI-readable documentation that let anyone at Manifest ask a data question and trust the answer, a v1 agent on BigQuery already exists to build on

• Ship the measurement backbone for growth: one lead-source taxonomy across all traffic, multi-touch attribution, cohorted LTV:CAC

• Kill manual reporting: weekly and monthly business reviews generated from live data instead of hours of hand-assembled pulls

• Lead and level up a team of data engineers: run one prioritization queue across marketing, sales, RevOps, and finance, set the delivery cadence and quality bar, and keep shipping dbt yourself

• 7+ years across data engineering and analytics at fast-growing companies, with end-to-end ownership of real production data systems

• Expert SQL and Python, deep hands-on experience with dbt and a modern cloud warehouse (we run BigQuery, Airbyte, and DataStream CDC)

• Go-to-market data depth: CRM (HubSpot or Salesforce), paid media platforms, web and product analytics, attribution

• AI-native by default: AI tools are core to how you build daily, and you’ve shipped data products that LLMs or agents consume, semantic layers, AI-readable documentation, or conversational analytics

• Player-coach: you’ve led or tech-led a small team while staying hands-on

• New York City, in-office 5 days/week

You want to be at the tip of the spear of a once-in-a-generation shift in how professional services are delivered. You want to own a function end to end at a fast-moving company. And you want to build in person, alongside a great group of people.

• You need a mature platform team and clean upstream data to be productive

• You want to be purely a manager or purely an IC, this role is deliberately both

• You’re looking for remote or hybrid, we build in person in NYC