Job description

Lead Data Engineer About us: At Fullbay, our mission is simple — to create safer roads for our families and yours. As leaders in the heavy-duty repair industry, we power shops with technology that helps them run smarter and more efficiently. As an AI-First company, we invite artificial intelligence to eliminate friction, spark innovation, and drive efficiencies in every conversation— for our teams and our customers. Fullbay is the number one cloud-based shop management software for commercial repair shops and is growing fast. This is an exciting opportunity to join a high-performing team and help shape the next phase of growth for the company. Position Overview: The Lead Data Engineer owns Fullbay's data platform end to end. Fullbay runs a Snowflake data warehouse that serves organizational reporting across two live products and acts as the primary read plane for AI agents. This role owns the architecture of that platform, builds it out hands-on, and holds the authority to set standards and revise the design as the business changes. At its core this is an enablement role. Business users and AI agents increasingly self-serve against Fullbay data, and the Lead Data Engineer is what makes that self-service trustworthy, through certified metric definitions, a well-governed semantic layer, and disciplined platform standards. The role reports directly to the VP of IT with the charter to set data standards company-wide. The Right Wrench for the Job Every heavy-duty shop runs on one set of specs. Torque values, part numbers, and service intervals only work when the tech, the service writer, and the parts counter all read from the same manual. When two people have two different numbers for the same bolt, the truck comes back. That's this role, but for the numbers Fullbay runs on: the definitions behind every report, for two live products and for the AI agents that now read the data as readily as people do. You're the right fit if you've owned a production data platform and know the difference between a metric that's documented and one that's trusted. You can declare a grain and defend it in the morning, ship tested SQL through version control by noon, and tell an executive no, with the reasoning, before the end of the day. You treat documentation as the deliverable, because you may be the only person who knows how something works, and you're curious about what it takes to make company data something agents can rely on. This isn't the role for someone who wants to build reports on request, or who needs a data team, a finished design, and a scoped backlog to lean on. If your instinct is to say yes to every ask and sort out the definition later, this isn't your shop. But if you're the kind of person who will set the standard, hold the line on it, and write it down so the next person can pick it up without a phone call, we'd like to talk. Primary Duties & Responsibilities: Certified Definitions & Semantic Layer: Own the metric and entity definitions the whole company reports from and serve as the final arbiter when functions disagree on a definition. Keep documentation current enough that a business user finds the right answer without needing to ask — this is the center of the role, not a component of it. Gold Layer Ownership: Build and extend Fullbay’s gold layer hands-on, writing SQL and transformation code in version control with automated tests. Identity Resolution: Own identity resolution across our Classic, Next, and Salesforce platforms, including crosswalk logic, survivorship rules, and platform-of-record determination over time. A permanent responsibility, not a one-time migration task. Snowflake Platform Ownership: Own Snowflake’s role hierarchy and grants, row access and masking policies, warehouse sizing, and cost attribution and spend. Agent Enablement: Design curated access paths for AI agents as first-class data consumers, including per-agent identities and grants, a registration pattern, and a retention policy for agent-produced data. Source Ingestion: Onboard new data sources to documented patterns, own schema drift and deletion detection, and partner with engineering on source schema changes. Vendor Direction: Scope and direct the retained architecture consultant’s ongoing work — writing specs, reviewing deliverables against approved standards, and rejecting nonconforming work. Self-Serve Enablement: Provide guidance and office hours for business users and AI builders to self-serve against the data platform. This role explicitly does not build reports on request. Documentation: Treat documentation as a core deliverable, not an afterthought. With no second data employee, documentation is Fullbay’s continuity plan for this function. Adheres to all confidentiality and compliance regulations. Performs other duties as assigned. Minimum Education & Work Experience: 7+ years of data engineering experience, including demonstrated ownership of a production data platform, required. Deep dimensional modeling experience required: able to declare a grain, defend historization choices per attribute, and articulate a restatement policy. Experience with Snowflake (or a comparable cloud data warehouse) beyond SQL — warehouse strategy, cost management, RBAC, and environment design — required. Experience building transformations as version-controlled code with automated tests and CI required. Bachelor’s degree in computer science, data engineering, or a related field, or equivalent work experience. Experience with change data capture and incremental extraction from application databases required. Experience with entity resolution across systems with independent identifiers required. Key Skills and Qualifications: Comfortable being the only person who knows how something works, and documents accordingly. Willing to say no to a vendor, an app team, or an executive, and ability to explain why. Strong written communication skills; able to arbitrate cross-functional definitional disagreements clearly and diplomatically. Nice to have: Experience serving AI or programmatic consumers of data, familiarity with the Salesforce object model, prior experience as a company’s first data hire, and prior experience directing outside vendors. What Makes This Role Unusual: Two live products — Classic and Next — supported permanently, not a migration to complete. AI agents as first-class consumers of data, alongside human reporting. Greenfield authority to set company-wide data standards, inside an architecture already designed by an outside firm. Direct line to the VP of IT, with the charter to set standards company-wide. Physical Demands and Work Environment: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions Regularly required to sit at a desk in front of a computer and use hands to finger, handle, or feel objects, tools, or controls (including a computer keyboard and operating a telephone), lift and/or move up to 10 pounds. Frequently requires the use of hands and arms for reaching, as well as the ability to walk and communicate effectively through speaking and listening. Specific vision abilities required by this position include close vision, color vision, and the ability to adjust focus. Noise level in the work environment is usually moderate. Type on a computer keyboard and look at a computer monitor and operate a cell phone or a computer-based phone.

Requirements

Must-haves

Lead Data Engineer
The Right Wrench for the Job
Gold Layer Ownership: Build and extend Fullbay’s gold layer hands-on, writing SQL and transformation code in version control with automated tests.
Snowflake Platform Ownership: Own Snowflake’s role hierarchy and grants, row access and masking policies, warehouse sizing, and cost attribution and spend.
Agent Enablement: Design curated access paths for AI agents as first-class data consumers, including per-agent identities and grants, a registration pattern, and a retention policy for agent-produced data.
Source Ingestion: Onboard new data sources to documented patterns, own schema drift and deletion detection, and partner with engineering on source schema changes.
Vendor Direction: Scope and direct the retained architecture consultant’s ongoing work — writing specs, reviewing deliverables against approved standards, and rejecting nonconforming work.
Self-Serve Enablement: Provide guidance and office hours for business users and AI builders to self-serve against the data platform. This role explicitly does not build reports on request.
Documentation: Treat documentation as a core deliverable, not an afterthought. With no second data employee, documentation is Fullbay’s continuity plan for this function.
Adheres to all confidentiality and compliance regulations.
Performs other duties as assigned.
7+ years of data engineering experience, including demonstrated ownership of a production data platform, required.
Deep dimensional modeling experience required: able to declare a grain, defend historization choices per attribute, and articulate a restatement policy.
Experience with Snowflake (or a comparable cloud data warehouse) beyond SQL — warehouse strategy, cost management, RBAC, and environment design — required.
Experience building transformations as version-controlled code with automated tests and CI required.
Bachelor’s degree in computer science, data engineering, or a related field, or equivalent work experience.
Experience with change data capture and incremental extraction from application databases required.
Experience with entity resolution across systems with independent identifiers required.
Comfortable being the only person who knows how something works, and documents accordingly.
Willing to say no to a vendor, an app team, or an executive, and ability to explain why.
Strong written communication skills; able to arbitrate cross-functional definitional disagreements clearly and diplomatically.
Two live products — Classic and Next — supported permanently, not a migration to complete.
AI agents as first-class consumers of data, alongside human reporting.

Nice-to-haves

Nice to have: Experience serving AI or programmatic consumers of data, familiarity with the Salesforce object model, prior experience as a company’s first data hire, and prior experience directing outside vendors.

Application prep

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Keywords to mirror

aisql

Platform: bamboohr
Effort: medium

Benefits

Benefits detected in the listing.

Vision