This is a player-coach role. You will lead a team of data engineers. You set priorities and hold the bar, and you stay close enough to the work to shape architecture, review designs, and write code when it helps. You are accountable for the platform's outcomes. Your team owns the technical design and build of the secure access path. AI agents are first-class users of our platform, and we build with agents ourselves.
Strategic & Tactical
Lead and grow the team. Hire, develop, and retain strong data engineers. Set clear expectations, give honest feedback, and build career paths so no system depends on one person.
Set direction and deliver. Set the roadmap in line with company objectives, weigh trade-offs openly, and be clear about what the team is not doing. Deliver cross-team projects on time and on budget.
Own the data architecture. Set the target architecture for ingestion, modeling, the semantic layer, and governance. Review designs and write code when it helps.
Own the platform outcomes. Be accountable for reliable pipelines with clear SLAs, one consistent set of metric definitions, and agent-ready data whose answers trace back to source.
Direct the access path. Be accountable for the secure serving layer and APIs. Your team designs and builds them, and you set priorities and standards.
Build governance in. Experience preparing governed data for AI consumers, with answers that trace back to their source.
Manage vendors. Evaluate data platform and tooling vendors, negotiate and sign contracts within your approval limit, and keep warehouse and tooling costs in check.
Partner across the company. Work with finance, operations, sales, marketing, and product to understand their evolving data needs, and bring concrete recommendations to business owners.
Qualifications
10+ years in software or data engineering, including 5+ years managing engineers.
A record of hiring well, developing people, and building strong teams.
Data Architect depth: you have designed enterprise data architecture (warehouse, modeling, lineage, governance) and led architecture reviews.
Hands-on depth in a modern warehouse and transformation framework (e.g., Snowflake, BigQuery, dbt) and SQL, with enough fluency in one backend language (e.g., Python) to review and contribute.
Demonstrated agentic engineering beyond prompting: you use coding agents in your own work and have brought agentic practices to a team.
Working knowledge of production APIs, authorization and access control, and PII handling.
A record of delivering data platform projects that span multiple teams, including deciding what not to build.
A history of building consensus with partners outside engineering, including finance, capital markets, and accounting.
Experience preparing governed data for AI consumers, with answers that trace back to their source.
Experience evaluating vendors and negotiating contracts.
Employment is contingent upon the successful completion of a background check.
Equal Employment Opportunity
Palmetto embraces diversity and is an Equal Employment Opportunity employer. Employment is decided on the basis of qualifications, merit, and business need. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or any other status protected under federal, state, or local law.
To ensure a fair evaluation, we may use AI to assist in sorting applications, but all final decisions are made by our hiring team and no candidate dispositions are automated. We will keep your information on file for four years from the date of your application. For detailed information about how we handle your data and our use of AI, please review our full privacy policy.
For more about our Privacy Policy, visit: https://palmetto.com/privacy-policy
