Own the enterprise data and AI platform roadmap and architecture, and design, build, secure, and operate infrastructure supporting reporting, automation, and AI applications. Lead technical work across staff and engineering partners and chair the Data Governance Committee.
Responsibilities:
- Design and maintain dbt models, the semantic layer, and data quality tests.
- Administer PostgreSQL, including performance, backups, recovery, and monitoring.
- Run automated, repeatable pipeline deployments.
- Manage security, access controls, data protection, encryption, and credentials.
- Design secure AI integrations and guide AI applications and automations from prototype to production.
Requirements: 5+ years in data engineering, database administration, data architecture, or a similar role; strong SQL and PostgreSQL administration; experience with dbt or equivalent and orchestration tools; working knowledge of Azure or similar cloud platforms; Python pipeline and automation skills; CI/CD experience; hands-on AI and LLM tooling experience; security experience; and ability to lead cross-functional groups and communicate technical decisions.
Preferred: Claude Code, MCP, containers, Salesforce, ServiceNow, Paylocity, Sage Intacct, data governance, or managed services experience.
Compensation: Starting at $140,000 per year; final salary depends on experience, skills, qualifications, and other factors.