Senior Data Engineer

Your AI Department; San Francisco (CA); Hybrid; USD 180,000 - 260,000; Full time

Job summary

Your AI Department in the San Francisco Bay Area is seeking a Senior Data Engineer to architect scalable data platforms, design production pipelines, and enable AI readiness across complex data landscapes.

You will stitch ERP, CRM, spreadsheets, and inbox data, connect disparate systems, and build real-time data foundations that empower autonomous workflows and AI agents to reason with trustworthy data.

Qualifications

• 6+ years of experience in data engineering across enterprise environments.
• 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 experience integrating data from ERP/SAP, Salesforce, NetSuite, and other systems.

Responsibilities

• Lead legibility and eligibility audits to assess AI readiness of client data.
• Stitch fragmented data environments connecting ERP, CRM, spreadsheets, and inbox data.
• Design and deploy production data pipelines (batch and streaming) across cloud environments.
• Eliminate PDF data bottlenecks by tracing data to source systems and building direct connections.
• Collaborate with AI Solutions Engineers to support agent-level reasoning on the data layer.

Skills

SQL

Python

Data orchestration (Airflow)

Data orchestration (Dagster)

Data orchestration (Prefect)

Real-time data pipelines

Enterprise data integration

Communication to executives

Tools

Airflow

Dagster

Prefect

BigQuery

Snowflake

Redshift

GCP

AWS

Salesforce

NetSuite

Job description

# Senior Data EngineerBay Area (Remote-Flexible)Full-timeData EngineeringWe are seeking an exceptional problem solver who operates at the intersection of data architecture, pipeline engineering, and AI readiness. The ideal candidate looks at a company's messy data landscape and sees the path to making it legible and accessible to autonomous systems.Most AI projects fail because the data is trapped in dashboards, buried in email attachments, or scattered across systems that have never been connected. You fix that.## 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 UsOur 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.## CompensationCompetitive base + performance-based comp tied to client outcomes.## Apply for this roleFill out the form below and we'll be in touch.