Senior Manager, Data Engineering

Location

This position will be remote based in the United States.

Reporting

This position will report to the VP, Engineering.

Summary of Role

You will lead the team that makes Palmetto's data usable by product teams, finance, operations, partners, and AI agents. Today much of our data lives in reporting dashboards. Your team builds the platform that lets products and AI tools use that data directly, with the right access controls, audit trails, and speed. The result is one consistent view of the whole customer journey, from sales and lending to installation, interconnection, and years of production data.

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.