Job descriptionWe9re seeking a Head of Data to join our Operations team and own the intelligence layer that sits across everything we build. Alternative Payments sits on a substantial and strategically valuable data asset, accounting data, payment data, and rich operational data from across the business.
This is a player-coach role. You will set the
architecture vision and own the data roadmap, but you will also roll up your sleeves by reviewing and contributing to code, solving data quality issues, and working directly with the data engineering team.
This role is available to candidates eligible to work in the
US, hybrid in New York.What you9ll doA key challenge of this role is balancing reactive work (data quality, stakeholder requests, system syncs) against executing the longer-term data strategy. You will own:
Data Strategy & Infrastructure- Own the full data infrastructure and architecture: pipelines, data models, gold/silver/bronze layer design, and real-time vs. batch tradeoffs.
- Develop a clear, actionable data strategy and own the process of getting buy-in across leadership, engineering, and product to execute it.
- Bridge the gap between technical data engineering and business context, translating leadership9s strategic questions into queryable, actionable data products.
- Establish data governance, quality standards, and observability practices; ensure data lineage, security, and quality control are baked into the architecture, not added as an afterthought.
- Lead complex data projects requiring entity resolution and enrichment at scale, using deterministic rules, fuzzy matching, and ML-based approaches to unify multi-source data
- Prepare datasets and feature pipelines for machine learning workflows; prototype and implement predictive models that leverage unified datasets.
Analytics & Self-Serve Insights- Move the organization beyond dashboards toward self-serve analytics, insight generation, and data-driven recommendations that are accessible to humans, agents, and partners.
- Own data across both product data (what users do in the platform) and operational data (Salesforce, Zendesk, internal tooling), ensuring both feed into a coherent intelligence layer.
- Own the data product roadmap for external-facing analytics from scoping and architecture through to delivery, coordinating across data engineering and product to ship partner-facing features that surface clean, structured, and actionable insights.
- This includes leading complex, cross-functional data projects end-to-end: defining requirements, driving alignment, and ensuring the underlying data layer is accurate, performant, and built for non-technical consumption at scale.
AI Collaboration- Ensure the right data is available, clean, and structured so the AI engineering function can build and ship AI features confidently.
- Build toward a data layer that is AI-queryable: structure data so it can be consumed by agents, embedding models, and LLM-powered retrieval systems and find the right balance between unstructured and structured data.
- Collaborate closely with the engineering and ops teams to ensure data architecture decisions are upstream-compatible with the company9s AI product roadmap.
- Stay close to the evolving AI landscape so you can be a credible thought partner to the teams building on top of your data platform.
What you9ll bring- 8+ years of experience in data engineering, data architecture, analytics, or a closely related field, with at least 2 years in a senior leadership role.
- Strong programming proficiency in Python and SQL. You can review and contribute to code, not just manage engineers who write it.
- Deep technical fluency with data infrastructure end-to-end: from ingestion and pipeline design to serving layer and data model optimization.
- Proven experience with ML-based data enrichment and large data sets, and entity resolution at a meaningful scale, you have real opinions about where deterministic approaches break down and where ML is required.
- Fluency with AI data patterns: you understand what it means to structure data for retrieval-augmented generation, embedding search, and agent-based consumption.
- Strong business context: comfortable in a leadership conversation about commercial strategy, not just a technical one about pipeline architecture.
- A proactive mindset with the ability to drive projects independently in a high-ambiguity environment.
Nice to have- Experience at a fintech, payments, or data-rich vertical SaaS company; familiarity with PSA, accounting, or payments data is a strong plus.
- Track record working across both product data (user behavior in a platform) and operational data (CRM, ticketing, internal tooling).
- Familiarity with vector databases, embedding pipelines, or structured data prep for LLM-based retrieval.
- Experience evaluating data assets for commercial or partner-facing applications.
- Comfort working in fast-paced, start-up environments where the data strategy is still being defined.
What We Offer- Competitive salary tailored to your experience, skills, and expertise.
- The total compensation range for this role is $175k - $200k, plus equity. The range displayed on each job posting reflects the approximate total target compensation for the position. Within the range, individual pay is determined by factors including relevant skills, experience, education/training.
- Equity opportunities so you can share in our growth and success.
- Unlimited PTO and flexibility when you need it the most.
- Yearly learning & development stipend to help you grow and do your best work.
