{"id":4046294,"url":"https://alion.io/job/dealpath-data-products-lead","title":"Data Products Lead","company":{"id":58524,"name":"Dealpath","domain":"dealpath.com","url":"https://alion.io/company/dealpath","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"Sales","role_family":"Sales","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":190000,"max":215000,"currency":"USD","period":"year","gross":null,"usd_annual":215000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Claude","optional":false},{"name":"Cursor","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Looker","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Agentic Workflows","optional":true},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-11-10T23:13:48Z","employer_posted_date":"2026-11-10","last_verified_at":"2026-11-11T13:56:29Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Data Products Lead\nDealpath is looking for a Data Products Lead to join our growing team and bring our powerful SaaS platform to institutional investment management firms.\nThis is a revenue role. You will own data products from the first query to the first paying customer and beyond, working directly with our CFO and our business development leaders. You will define what we sell, build it, put it in front of customers, and measure whether they come back and pay.\nYou're excited about this opportunity because you will:\nTurn reporting into a product. Replace static reports with self-serve, permissioned analytics. Design how it is packaged and instrument usage so we know who logs in, who comes back and who converts.\nBuild and launch benchmark data products. Create market benchmarks from anonymized, aggregated data. Own the methodology, refresh SLAs and the quality bar a paying data customer will hold us to.\nOwn the data product layer. Design governed, multi-tenant models in Snowflake and dbt and the semantic layer in Omni: metric definitions, tests, freshness and correctness alerting, tenant isolation and entitlements.\nDeliver data where clients work. Package data for delivery outside a dashboard: APIs, data feeds, warehouse shares and MCP tools. Build in the entitlements, usage metering and SLAs a paying data customer expects.\nNormalize messy market data. Data arrives from many sources in different shapes. Resolve it into consistent entities customers can compare, and catch data gaps before a customer does.\nValidate demand and pricing with the commercial team. Run design partnerships, time-boxed trials and willingness-to-pay tests. Bring the evidence that decides what we build, how we package it and what we charge.\nBe the analytics partner to the business development team. Own the recurring analysis they rely on, including partner reporting, pilot success criteria and revenue attribution, so they can spend their time with customers.\nMake it last. Write the metric definitions, document the usage rules for each product and leave work that others can maintain and extend.\nHow we think about AI for this role\nWe expect you to build with AI every day. You will use AI tools to write and test code, prototype products and document your work, and you will judge when AI output is accurate enough to put in front of a customer. You will also design data so AI agents, ours and our clients', can query it reliably.\nWhat success looks like in your first year\nCustomers use our data products in place of static reports, and come back on their own.\nAt least one benchmark product is in market with paying or committed customers.\nAt least one data product reaches clients through an API, feed or AI agent, not only a dashboard.\nData products are a measurable part of company revenue, with clean attribution.\nWe're excited that you have:\nCommercial instinct. You can sit with a customer, work out what they would pay for, and turn it into a product, a metric and a price test.\nClear writing and speaking. You can explain a methodology to a broker, a product spec to an engineer and a result to a board member.\n A bias to ship. You thrive in 0 to 1 work at a growth-stage company and ship in weeks, not quarters.\nQualifications\n8+ years in analytics, data science or analytics engineering, including at least one customer-facing data product you shipped to production and supported.\nExpert SQL and strong Python. Hands-on with dbt or Dataform, a cloud warehouse (Snowflake, BigQuery or Databricks) and a semantic layer or BI tool (Omni, Looker or similar).\nDaily, hands-on use of AI tools (for example Claude, Cursor or similar) and LLMs to write code, test and ship, and experience evaluating their output.\nDelivered data to customers through APIs, data feeds or warehouse sharing (for example Snowflake Secure Data Sharing), with entitlements and usage tracking, not only through dashboards.\nOwned a company's metric layer end to end: modeling, lineage, governance, tests and adoption by executives.\nStatistical judgment: cohort and retention analysis, segmentation, experiment design, forecasting, and knowing when a number is noise.\nBachelor's degree in computer science, statistics, economics or a related field, or equivalent experience.\nNice to haves\nCommercial real estate, proptech, marketplace or two-sided network data.\nEmbedded analytics or data sold as its own product.\nData privacy and aggregation design: de-identification, minimum cell sizes, entitlements.\nBuilt agentic workflows, MCP servers or retrieval on top of structured data.\nThe Perks & Culture\nMedical, dental, & vision insurance coverage options\nFlexible Spending Account\nPaid Parental Leave\nHybrid Work Policy, 3 days in office (Tues/Wed/Thur).\n401(k)\nCompany sponsored commuter benefits\nFlexible time off policy\nCatered lunches and snacks\nMonthly wellness reimbursement\nThe estimated base pay range for California candidates is $190,000 - $215,000.\nYour compensation will be based upon several factors including your experience, qualifications, education, location, and the skills assessed in Dealpath's interview process. Your actual compensation will be confirmed in writing at the time of offer.\nDealpath's compensation ranges are determined by current market data, so compensation data posted on our job posts may change as new market data becomes available.\nAbout Dealpath\nDealpath is the world's largest and most trusted AI-powered operating system for real estate investing. To date, the platform has powered more than $10 trillion in transactions, partnering with hundreds of firms, including leading global institutions such as Blackstone, Nuveen, LaSalle, CBRE IM, MetLife, Newmark, Oxford Properties, New York Life, UBS, Manulife, DWS, and Principal.\nBy bringing together the only private exchange for institutional real estate listings, investment data, and intelligent execution workflows into a single platform, Dealpath enables firms to capture more opportunities, make faster decisions, execute efficiently, and deliver superior returns.\nOur company is led by an experienced team and backed by a combination of top tier venture capital firms and strategic industry partners including: Blackstone, Nasdaq, 8VC, JLL Spark, WTI, GreenSoil Investments, LeFrak, Milstein, Bechtel, and Morgan Stanley Expansion Capital.\nWe value your voice! If you get excited about solving real business challenges and working closely with other smart folks in a winning culture, we'd love to meet you!\nEqual Opportunity and Interview Process Notices\nAt Dealpath, we hire for talent, curiosity, and drive, not background or identity. We're committed to building a team that reflects the full range of perspectives and experiences, and we welcome applicants regardless of race, color, religion, gender identity or expression, sexual orientation, national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by law.\nIf you need an accommodation at any point in the hiring process, please reach out to us at . We're happy to help.\nPursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.\nDealpath participates in E-Verify. Upon hire, we will verify employment eligibility with the U.S. Department of Homeland Security, as required by law.\nDealpath conducts interviews via video conference. To support our interviewers with accurate note-taking, we may use AI-assisted transcription tools during your interview sessions. By participating in the interview process, you acknowledge that interviews may be recorded or transcribed using these tools for note-taking purposes only. 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Docs: https://alion.io/developers"}}