Lead Marketing Data & Analytics Engineer

About Jetson Jetson is on a mission to accelerate the transition of 100 million homes across North America away from fossil fuels toward sustainable energy use. We believe in a future that is 100% electric and 100% better. Homes are one of the largest sources of carbon emissions, yet adoption of solutions like heat pumps remains slow due to cost and complexity.

Jetson is solving this by building the first fully vertically integrated home electrification company — making clean energy simple, transparent, and affordable. We rely heavily on technology, automation, and data to scale this impact. At Jetson, we value people who are excellent at their craft, curious about new tools (including AI), and motivated to continuously improve how work gets done.

The Opportunity Jetson has gone from $20M to $100M in run-rate sales this year. We're on track to end the year around $250M and scaling toward $1B. That growth is being driven by a marketing org that is getting more sophisticated every quarter — performance marketing across Meta, Google, direct mail, OOH, and CTV; a strong in-house creative studio; an emerging partnerships function; and an experimentation and lifecycle team that needs sharper attribution and faster feedback loops to keep compounding.

The data layer underneath all of that is what unlocks the next leg of growth. We've built out a real data lake — Iceberg on AWS Glue, dbt for transformation, Fivetran for ingestion, Metabase for BI. The core framework exists.

Meaningful work remains to refine it, fill the gaps, integrate the next wave of sources, and ensure the team has accurate real-time data they can trust. You'll own the marketing data lake end to end — the integrations that bring data in, the bronze/silver/gold models that shape it, the dashboards that surface it, and the analysis that turns it into decisions the team actually makes. This is a full-stack role.

On any given week you might be standing up a new Fivetran connector for a direct mail vendor, writing the dbt models to land it cleanly into our medallion architecture, building the Metabase dashboard for the performance team to use, and then pulling the analysis together to tell them whether the campaign worked. There's no handoff between the engineering and the analysis — you do both. You'll work closely with the performance marketing team (who'll lean on you for measurement and incrementality), the growth and experimentation team (who'll need experiment infrastructure and LTV models), and our core data engineering team (who own the broader platform you're building on top of).

What You'll Own The marketing data lake. Iceberg, Glue, dbt, Fivetran, Metabase. You own the bronze/silver/gold models, the schemas, the freshness, the cost, and the contract with downstream consumers.

If a number is wrong in a dashboard, you're the one who finds out why and fixes it at the source. Source integrations. Every new channel, vendor, or partnership comes with a new data source — Meta and Google Ads, HubSpot, direct mail vendors, CTV platforms, call tracking, utility and financing partners.

You stand up the Fivetran connectors (or write the Python when Fivetran can't), land the raw data in bronze, model it through silver and gold, and surface it where it needs to be. Attribution and measurement. Multi-touch attribution across paid, organic, direct mail, OOH, CTV, partnerships, referrals, and field sales.

Identity resolution across web, CRM, and offline conversions. You'll design and maintain the attribution models the team relies on day to day, and the incrementality work that informs bigger budget decisions. Experimentation infrastructure and readout.

Geo holdouts, conversion lift studies, direct mail incrementality, on-site experiments. You'll build the data infrastructure that makes them trustworthy — assignment logging, variant tracking, exposure data — and you'll do the analysis to tell the team whether the result is real. LTV, conversion, and channel ROI.