AI Data Engineer

Collective • San Francisco, CA

1d • Hybrid

About The Position

Most teams have the data they need but can’t access it. This role is here to fix that.
We're hiring a senior engineer to build an internal data agent: a system that lets anyone at the company act as their own data analyst. Individuals can ask questions in plain English and get back correct, decision-ready answers or dashboards.
This is not a traditional data role. You'll operate across AI systems, data infrastructure, and product engineering. You'll be responsible both for building a powerful system and for ensuring the data it relies on is clean, consistent, and reliable.
The problem space is wide open. We’re looking for a strategic operator to shape the technical direction, the data model, and system adoption.

Requirements

• You are a product engineer working in data
• You treat data models as part of the product, not a separate layer
• You have strong opinions on schema design, naming, and consistency
• You're comfortable identifying issues in production data and fixing them at the root
• You are an owner, not a participant
• You take vague, high-stakes problems and turn them into real systems
• You care about outcomes, not just implementation
• You have strong data experience
• Experience with data modeling, warehouses, and pipelines
• You're an exceptional builder
• You can go from idea → architecture → production
• You've built with LLMs, RAG, or agents in production
• You've shipped systems that people actually rely on
• You have influence
• You communicate effectively with both technical and non-technical stakeholders
• You can drive alignment across teams with competing priorities
• You're comfortable challenging existing systems and pushing for better approaches
• You have taste
• You know the difference between something that works and something people trust
• You make pragmatic tradeoffs without overengineering
• You move fast
• You default to action and iteration
• You're comfortable operating independently

Responsibilities

• Build an end-to-end analytics system
• Create a natural language interface over our entire data stack
• Enable anyone to run complex analyses without writing SQL
• Own and improve the data layer
• Collaborate with product engineering to design and evolve clean, consistent data models
• Identify inconsistencies in the core schema and resolve them at the source
• Build and maintain data pipelines
• Own the reliability of our data infrastructure end-to-end
• Debug and fix broken systems (e.g. dbt models, pipeline failures)
• Make it easy to integrate new data sources into the data warehouse
• Develop agent infrastructure
• Build retrieval, planning, and execution systems on top of real data
• Support multi-step reasoning and analysis workflows
• Integrate into internal tools
• Make it trustworthy
• Ensure outputs are correct, consistent, and explainable
• Build evaluation loops, monitoring, and guardrails
• Eliminate ambiguity in metrics, definitions, and sources of truth
• Handle permissions, sensitive data, and edge cases
• Drive adoption
• Work directly with teams across EPD, Member Operations, Legal, and more
• Drive alignment on data definitions and system usage
• Turn this into the default way people interact with data

Benefits

• Hybrid Work Model: Based in San Francisco with a balance of in-office and remote flexibility.
• Fresh Lunch: Provided on in-office days.
• Commuter Support: $150 monthly reimbursement for transit expenses.
• Health & Wellness: $200 quarterly reimbursement to support your well-being.
• Time Off: Flexible PTO plus 14 company holidays.
• Comprehensive Coverage: 100% medical, dental, and vision for employees; 75% coverage for dependents.
• Parental Leave: 16 weeks fully paid.
• Retirement & Ownership: 401k plan plus an equity package.
• Team Connection: Quarterly virtual events and an annual in-person summit.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 101-250 employees