Staff Data Engineer

Description

The company's data spans the full customer journey, from sales and lending through installation, interconnection, and years of system production. The role owns the technical design of the data platform that serves the company's products, partners, and AI agents.

The goal is one governed, trustworthy view of the business, with every metric defined once so dashboards, notebooks, and agents all return the same result. The work also includes a secure, authorized, auditable way for people and systems to use that data directly.

This is a senior individual-contributor position. You will set technical direction, write foundational code, and work closely with the core platform and product teams. AI agents are primary users of the platform, and the team builds with them daily.

Responsibilities

• Model the business by building and owning data products, from bronze to gold, that give analysts, engineers, product teams, partners, and AI tools data they can trust.
• Shape the semantic context, documentation, and interfaces so agents answer from governed definitions, with every answer traceable to its source.
• Treat classification, masking, access policy, and change control as code, and prepare the platform for SOC 2 and related compliance audits.
• Run ingestion and orchestration as code, including CI/CD, observability, alerting, and SLAs.
• Work with finance, operations, product, and engineering to track how their data needs change.
• Design and run the secure, authorized, low-latency interface that products, partners, and agents use to consume data.
• Review code, mentor teammates, and provide engineering teams with templates and CI checks for shipping trusted data.

Requirements

• You have 8+ years in data engineering, including time at Staff or lead level owning a platform used by several teams.
• You have deep SQL and Python skills.
• You understand analytical warehouse fundamentals such as schema design, query plans, and distributed computing, ideally in Snowflake or BigQuery.
• You have deep experience with dbt or a similar transformation framework such as SQLMesh or Dataform.
• You have experience orchestrating ETL with tools such as Fivetran or Airflow.
• You have infrastructure-as-code and container orchestration experience on AWS, GCP, or Azure.
• You go beyond prompting with coding agents, running them in loops checked by specs and tests, and you keep up with new tools.
• You have written design docs that resolved cross-team architecture questions and can explain technical work clearly to non-technical partners, in writing and in conversation.
• You understand API design, authentication and authorization (such as OAuth/OIDC and RBAC), and PII handling.
• Experience with reporting tools such as Looker or Hex is a plus.

Conditions

This is a remote position based in the United States.

The role reports to the Senior Manager, Data Engineering.