Senior Manager, Data Engineering

Palmetto Clean Technology

20h•Remote

About The Position

Palmetto is hiring a Senior Manager, Data Engineering to lead the team responsible for making company data directly usable by product teams, finance, operations, partners, and AI agents. The team will build a secure, governed data platform and access path that gives users a consistent view of the customer journey, from sales and lending through installation, interconnection, and ongoing production data. This is a player-coach role. The manager leads and develops data engineers, sets priorities and standards, and remains close to technical work by shaping architecture, reviewing designs, and contributing code when useful. The role is accountable for platform outcomes, including reliable pipelines, consistent metric definitions, traceable agent-ready data, and secure serving layers and APIs. The position sets the data platform roadmap in alignment with company objectives, leads cross-functional delivery, owns architecture across ingestion, modeling, the semantic layer, and governance, and manages data platform vendors and costs. The manager partners with business teams to understand evolving data needs and provide concrete recommendations. This position is remote within the United States and reports to the VP, Engineering.

Requirements

10+ years of experience in software or data engineering.
5+ years of experience managing engineers.
A record of hiring well, developing people, and building strong teams.
Experience designing enterprise data architecture, including warehousing, modeling, lineage, and governance, and leading architecture reviews.
Hands-on experience with a modern data warehouse and transformation framework such as Snowflake, BigQuery, or dbt, and SQL.
Fluency in at least one backend language, such as Python, sufficient to review and contribute to code.
Demonstrated agentic engineering beyond prompting, including using coding agents personally and bringing agentic practices to a team.
Working knowledge of production APIs, authorization and access control, and PII handling.
A record of delivering data platform projects spanning multiple teams, including deciding what not to build.
Experience 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.

Responsibilities

Hire, develop, and retain data engineers; set expectations, provide feedback, and build career paths.
Set the team roadmap in alignment with company objectives, make trade-offs clear, and deliver cross-team projects on time and within budget.
Own the target architecture for data ingestion, modeling, the semantic layer, and governance; review designs and contribute code when helpful.
Ensure reliable data pipelines with clear SLAs, consistent metric definitions, and agent-ready data whose answers trace back to source.
Set priorities and standards for the secure data serving layer and APIs, which the team designs and builds.
Build governance into data prepared for AI consumers.
Evaluate data platform and tooling vendors, negotiate and sign contracts within the approval limit, and manage warehouse and tooling costs.
Partner with finance, operations, sales, marketing, product, and other business stakeholders to understand data needs and offer recommendations.