LocationThis position will be remote based in the United States.
ReportingThis position will report to the Senior Manager, Data Engineering.
Summary of Role You will own the technical design of the data platform that powers Palmetto's products, partners, and AI agents. Our data spans the whole customer journey: sales, lending, installation, interconnection, and years of system production. You will turn it into one governed, trustworthy view of the business, with each metric defined once so every dashboard, notebook, and agent returns the same answer. You will also build the secure, authorized, auditable path that lets people and systems use that data directly.
This is a high-leverage individual-contributor role. You'll set technical direction, write foundational code, and work closely with core platform and product teams. AI agents are first-class consumers of our platform, and we build with them every day.
Strategic & Tactical- Model the business. Build and own data products that deliver trustworthy data, from bronze to gold, for analysts, engineers, product teams, partners, and AI tools.
- Make data agent-ready. Shape the semantic context, documentation, and interfaces that let agents answer from governed definitions, with answers that trace back to source.
- Build governance in. Treat classification, masking, access policy, and change control as code, and prepare the platform for SOC 2 and related compliance audits.
- Build and run pipelines. Operate ingestion and orchestration as code, with CI/CD, observability, alerting, and SLAs.
- Communicate. Partner with finance, operations, product and engineering to understand how their data requirements are evolving.
- Build the access path. Design and operate the secure, authorized, low-latency interface through which products, partners, and agents consume data.
- Raise the bar. Review code, mentor teammates, and give engineering teams templates and CI checks to ship trusted data.
Qualifications- 8+ years in data engineering, including time at a Staff or lead level owning a platform used by multiple teams.
- Deep experience in SQL and Python.
- Strong database fundamentals in a modern analytical warehouse (e.g., Snowflake, BigQuery): schema design, query plans, distributed computing.
- Deep experience with dbt or an adjacent transformation framework (e.g., SQLMesh, Dataform).
- Experience with ETL orchestration (e.g., Fivetran, Airflow).
- Infrastructure as code and container orchestration on a major cloud (AWS, GCP, or Azure).
- Demonstrated agentic engineering beyond prompting: you run coding agents in loops checked by specs and tests, and stay curious about new tools.
- Design docs that settled cross-team architecture questions, and clear written and verbal communication with non-technical partners.
- Working knowledge of API design, authentication and authorization (e.g., OAuth/OIDC, RBAC), and PII handling.
- Knowledge of reporting tools such as Looker and Hex is a plus
