Data Products Lead

Dealpath • San Francisco, CA

10h • $190,000 - $215,000 • Hybrid

About The Position

Dealpath is seeking a Data Products Lead to bring its SaaS platform to institutional investment management firms. This is a revenue role that owns data products from initial customer discovery through launch, monetization, and continued use, working directly with the CFO and business development leaders. The role defines, builds, packages, and commercializes data products, while measuring customer adoption and revenue.

The lead will transform static reporting into self-service, permissioned analytics; build benchmark products from anonymized, aggregated data; and own governed, multi-tenant data models and the semantic layer. They will deliver data through dashboards, APIs, feeds, warehouse shares, and MCP tools, with appropriate entitlements, usage tracking, and service levels. They will also normalize data from varied market sources, validate demand and pricing through customer research and trials, and provide recurring analytics for the business development team.

The role requires building with AI tools daily, evaluating AI-generated work before customer use, and structuring data so AI agents can query it reliably. Success in the first year includes customers independently returning to data products instead of static reports, at least one benchmark product in market with paying or committed customers, at least one product delivered through an API, feed, or AI agent, and measurable data-product revenue with clear attribution.

Requirements

• At least 8 years of experience in analytics, data science, or analytics engineering.
• Experience shipping at least one customer-facing data product to production and supporting it.
• Expert SQL and strong Python skills.
• Hands-on experience with dbt or Dataform, a cloud data warehouse such as Snowflake, BigQuery, or Databricks, and a semantic layer or BI tool such as Omni, Looker, or similar.
• Daily, hands-on use of AI tools and LLMs to write code, test, and ship, and experience evaluating their output.
• Experience delivering data to customers through APIs, data feeds, or warehouse sharing, with entitlements and usage tracking, rather than only through dashboards.
• Experience owning a company's metric layer end to end, including modeling, lineage, governance, tests, and executive adoption.
• Statistical judgment covering cohort and retention analysis, segmentation, experiment design, forecasting, and assessing whether a number is noise.
• Bachelor's degree in computer science, statistics, economics, or a related field, or equivalent experience.
• Commercial instinct and ability to determine what customers would pay for and translate that into a product, metric, and pricing test.
• Clear written and verbal communication for explaining methodologies, product specifications, and results to varied audiences.
• Bias to ship and ability to thrive in 0-to-1 work at a growth-stage company, delivering in weeks rather than quarters.

Nice To Haves

• Experience with commercial real estate, proptech, marketplace, or two-sided network data.
• Experience with embedded analytics or selling data as a standalone product.
• Experience in data privacy and aggregation design, including de-identification, minimum cell sizes, and entitlements.
• Experience building agentic workflows, MCP servers, or retrieval on top of structured data.

Responsibilities

• Replace static reports with self-service, permissioned analytics; package the offering and instrument usage, return visits, and conversions.
• Create market benchmark products from anonymized, aggregated data, owning methodology, refresh service levels, and data quality.
• Design and own governed, multi-tenant data models in Snowflake and dbt and the semantic layer in Omni, including metric definitions, tests, freshness and correctness alerting, tenant isolation, and entitlements.
• Deliver data outside dashboards through APIs, data feeds, warehouse shares, and MCP tools, including entitlements, usage metering, and service levels.
• Normalize data from multiple market sources into consistent entities customers can compare, and identify data gaps proactively.
• Run design partnerships, time-boxed trials, and willingness-to-pay tests with the commercial team; use evidence to guide product scope, packaging, and pricing.
• Own recurring analytics for business development, including partner reporting, pilot success criteria, and revenue attribution.
• Document metric definitions and product usage rules, and create work that others can maintain and extend.
• Use AI tools to write and test code, prototype products, and document work; assess whether AI output is accurate enough for customer use.
• Design data so internal and client AI agents can query it reliably.

Benefits

• Medical, dental, and vision insurance coverage options
• Flexible Spending Account
• Paid parental leave
• Hybrid work policy, with three days in the office (Tuesday, Wednesday, and Thursday)
• 401(k)
• Company-sponsored commuter benefits
• Flexible time off policy
• Catered lunches and snacks
• Monthly wellness reimbursement

What This Job Offers

• Job Type: Full-time
• Career Level: Senior