Senior Data Engineer

What You'll Do

• Lead Legibility and Eligibility Audits. Assess whether client data is structured enough for AI to reason with (Legibility) and whether AI can actually reach the source systems (Eligibility)
• Stitch fragmented data environments. You'll connect the ERP to the CRM to the spreadsheet to the inbox, building the unified data layer that AI agents need to operate
• Build the foundation for Cogs. Every autonomous workflow we deploy depends on clean, connected, real-time data. You build the infrastructure that makes Cogs possible
• Design and deploy production data pipelines (batch and streaming) across cloud environments
• Eliminate the "PDF problem." When a client's critical data is locked in static reports, you trace it back to the source system and build the direct connection
• Work with AI Solutions Engineers to ensure the data layer supports agent-level reasoning, not just dashboarding

You Should Have

• 6+ years of experience in data engineering, with significant time spent working across enterprise environments
• Strong proficiency in SQL, Python, and at least one modern data orchestration framework (Airflow, Dagster, Prefect)
• Deep experience with cloud data platforms (BigQuery, Snowflake, Redshift) and cloud infrastructure (GCP or AWS)
• Hands-on work integrating data from enterprise systems (SAP, Salesforce, NetSuite, legacy ERPs) where nothing is clean and nothing is documented
• Experience with real-time data pipelines and event-driven architecture
• The ability to explain data architecture decisions to a CEO in terms of business impact, not just technical correctness

Your Candidacy Is Stronger If

• You've done data migration or integration work during M&A, ERP rollouts, or digital transformation programs
• You have experience in manufacturing, logistics, healthcare, or professional services
• You've worked in consulting and understand the rhythm of client engagements: scoping, delivering, and iterating under time pressure
• You've built data infrastructure specifically to support ML or AI workloads in production

This Probably Isn't For You If

• You've primarily worked with clean, well-documented datasets in a single data warehouse
• You prefer building internal analytics dashboards over production data systems
• You want a stable, long-term codebase. Our work is engagement-based and every client environment is different
• You're not comfortable presenting technical findings to non-technical executives

About Us

Our team is former tech CEOs, exited founders, and AI engineers from Google, Meta, and Coinbase. We've built AI systems serving billions of users at large tech companies and scaled our own startups from zero. We understand constraints, P&Ls, and what it takes to make AI work inside companies that weren't born digital.

You'll work on real problems at real companies. Every system you build has a measurable dollar impact.

Compensation

Competitive base + performance-based comp tied to client outcomes.

Apply for this role

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