[Hiring] Lead Data Engineer @Fullbay

Role Description

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.

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.
• 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.
• 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.
• Documentation: Treat documentation as a core deliverable, not an afterthought.
• Adheres to all confidentiality and compliance regulations.
• Performs other duties as assigned.

Qualifications

• 7+ years of data engineering experience, including demonstrated ownership of a production data platform, required.
• Deep dimensional modeling experience required.
• Experience with Snowflake (or a comparable cloud data warehouse) beyond SQL 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.
• 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

• Regularly required to sit at a desk in front of a computer and use hands to finger, handle, or feel objects, tools, or controls.
• 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 include close vision, color vision, and the ability to adjust focus.
• Noise level in the work environment is usually moderate.