Sr. Data Engineer

Job Title: Sr. Data Engineer

Team: Engineering

Employment Type: Full-time, Salaried, Exempt

Reports To: Head of Engineering

Why Plug

• You'll own a piece of the biggest infrastructure opportunity in automotive.

The Opportunity

We are looking for a Senior Data Engineer to build the governed data layer at the center of Plug's AI-native strategy. Plug runs on Snowflake, dbt, and Fivetran. The infrastructure is in place; the governed layer is still being built. You will own the dbt transformation models and certified metric definitions that the business runs on, the ingestion pipelines that bring in OEM partner feeds, dealer data, auction signals, and HubSpot, and the data foundation that Rain Radar - our production EV pricing model - trains on. You will work with the dbt Semantic Layer as an interface for AI agents to query Plug's data with business context. You report to our head of engineering and work closely with our ML and data engineer.

What You’ll Do

Data Platform

• Own the dbt transformation layer - staging, intermediate, and mart models and MetricFlow definitions in the Semantic Layer - so Plug's business data is queryable by both humans and AI agents with the right business context.

• Build and maintain the ingestion layer: Fivetran pipelines and HubSpot integration for existing sources, and onboarding new ones - OEM partner APIs, dealer marketing feeds, auction signals, and attribution data - with monitoring and change control.

• Work with the dbt MCP server and Semantic Layer as Plug's AI agent data interface - no prior MCP experience required, but genuine excitement about the direction where agents replace dashboards as the primary way data is consumed.

• Maintain the ML feature store alongside our ML and data engineer: training data quality, schema stability, and documentation of the data foundation Rain Radar and future models depend on.

• Support internal data consumers by surfacing trusted datasets, enabling self-service reporting, and occasionally building reports to meet business needs.

Engineering

• Collaborate with the engineering team and ML and data engineer; be a strong voice in data architecture decisions and schema design reviews.

• Use agentic coding tools to write clear, tested, and maintainable transformation logic; bring a "capture everything" instinct to data collection decisions - think proactively about what should be captured, not just what is already specified.

• Own and contribute to data quality monitoring, alerting, and remediation - the data trust standard the whole organization relies on.

• Own production data pipelines, participate in incident response, and debug data issues across the stack.

• Actively raise the data engineering bar through thoughtful code review, documentation, and knowledge sharing - including how you use AI tools.

What You’ll Bring

• 5+ years building production dbt projects end-to-end: staging through mart layers, test coverage, schema change management, and ideally MetricFlow or semantic layer work.

• Genuine curiosity about AI-native data patterns - excited about the dbt Semantic Layer as an agent interface and building data infrastructure that AI agents query rather than humans navigating dashboards. No experience required; curiosity is.

• Cross-context ML awareness - has worked near an ML team and understands how upstream data quality decisions affect model training and feature quality, not just analytics accuracy.

• Snowflake or major cloud warehouse experience - schema design, role-based access control, and performance optimization.

• Fivetran or comparable ELT tool experience - managing pipelines and onboarding new sources with reliability and observability.

• Advanced SQL and Python for transformation logic, data quality checks, and pipeline automation.

• Experience integrating REST APIs and third-party data sources; comfortable with reliability patterns.

• Operates in agentic development workflows with a high quality bar for AI-generated output.

• Prior startup or small-team experience with a track record of owning data infrastructure end-to-end. Authorized to work in the US for any employer.

Compensation and Benefits

Annual salary: $180,000 - $210,000

Benefits & Perks:

• Health, Vision, and Dental insurance

• 401(k) plan

• Daily lunch stipend

• Equity (based on role and performance)

• 30-day remote work from anywhere policy

• Unlimited PTO

• Fully stocked kitchen

• Dog-friendly office

• Ongoing opportunities for growth and development