Sr. Data Engineer

Job Title: Sr. Data Engineer

Team: Engineering

Location: Onsite-Santa Monica, CA

Employment Type: Full-time, Salaried, Exempt

Reports To: Head of Engineering

Plug is an automotive fintech startup building the marketplace for electric vehicles. Consumers, dealers, and commercial partners trade in, sell, and auction used EVs through a platform built exclusively for electric, with nothing adapted from legacy automotive.

Consumers can get an instant cash offer in minutes, backed by data-driven pricing, battery state-of-health analysis, with pickup, payment, and title transfer handled end-to-end. Franchise and independent dealers across the United States bid in real time on inventory sourced directly from these consumers, dealers, and commercial partners. The result is a single platform that gives sellers a fast, fair exit and gives dealers a dedicated channel for sourcing used EV inventory.

Founded in 2023 and led by former Tesla executives, Plug has facilitated $100M in EV sales since launch and is backed by a $20M Series A from Lightspeed Venture Partners. We're building the most AI-native startup team in Los Angeles, full of operators, engineers, and ML researchers laying the transaction rails for the used EV market's exponential growth.

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

• You’ll work on a platform built exclusively for EVs, with nothing adapted from legacy automotive.

• You’ll be part of an AI-native company. We're rethinking how work gets done at a fundamental level.

• You’ll work directly with operators who have scaled multi-billion dollar businesses in automotive, EV, and marketplaces.

• You’ll have real ownership, high autonomy, and a direct line to company outcomes.

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 Hub Spot, 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.

Data Platform

• Own the dbt transformation layer - staging, intermediate, and mart models and Metric Flow 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 Hub Spot 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…