Data Analyst
Reads like an Analytics Engineer role: dbt models and clean tables.
San Francisco · San Francisco, California, United States
- Pay
$190,000–270,000/year · BaseAnnual period assumed — pay source
Compensation The estimated base salary for this role is between $190,000 - $270,000 Additionally, this role is eligible to participate in Meter's equity plan.
Read the full posting- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering — team source
Department: Engineering
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require sponsorship to work in the United States?
From the employer’s application form
What you’ll work on
Full postingShip canonical dbt models for accounts, opportunities, marketing touches and revenue
Build the attribution and funnel layer comparing partner, paid and outbound acquisition cost
Cut marketing channel analysis from a week of manual reconciliation to a query
Design schemas for new partner data sources
Write tests and review teammates' models to catch regressions before they ship
From the employer’s posting
Ship canonical dbt models for accounts, opportunities, marketing touches, and revenue that finance, sales, and marketing all use
Build the attribution and funnel layer that lets us actually compare the cost of acquiring a customer through partners versus paid versus outbound
Cut the time it takes the marketing team to answer "is this channel working" from a week of manual reconciliation to a query
Thursday is deeper IC work: designing the schema for a new partner data source
Friday you're reviewing a teammate's model and writing the test that catches the next regression before it ships
Tools in this posting
- SQL
- BigQuery
- dbt
- Snowflake
- Tableau
Source — Tool mentions in context
- You've been the analytical partner inside a GTM function — not just the analyst who delivered reports to one. You've sat in pipeline reviews, argued about attribution definitions, and built dashboards that executives actually use. - You write SQL the way most people write English. You reach for window functions, CTEs, and set operations without thinking. You can read someone else's 200-line query and find the bug in ten minutes. - You think in dbt. You have opinions about staging vs. marts, when to use incremental models, and what belongs in a snapshot. You've designed schemas that survived contact with a changing business.
- You build trust before you ship models. You know the dashboard nobody uses is worse than no dashboard at all. - You have deep experience with one or more of the following: Snowflake, BigQuery, Tableau, or other modern data stacks. Why Meter?
What you'll do in your first six months - Ship canonical dbt models for accounts, opportunities, marketing touches, and revenue that finance, sales, and marketing all use — replacing the four versions of "ARR by segment" floating around today. - Cut the time it takes the marketing team to answer "is this channel working" from a week of manual reconciliation to a query.
What a typical week looks like Monday morning you're pairing with a marketing lead on why their LinkedIn spend report doesn't match what finance recognized last quarter. Tuesday you're shipping a dbt PR that consolidates three definitions of "active customer" into one. Wednesday you're in the forecast review, watching the head of sales argue about coverage ratios, and you realize the underlying data has a fanout problem you can fix by Friday. Thursday is deeper IC work: designing the schema for a new partner data source. Friday you're reviewing a teammate's model and writing the test that catches the next regression before it ships. What we're looking for
- You write SQL the way most people write English. You reach for window functions, CTEs, and set operations without thinking. You can read someone else's 200-line query and find the bug in ten minutes. - You think in dbt. You have opinions about staging vs. marts, when to use incremental models, and what belongs in a snapshot. You've designed schemas that survived contact with a changing business. - You've worked across Salesforce, billing systems, marketing platforms, and product data, and you understand how they're each subtly wrong in their own way.
Posting record
Report an errorOpen 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026 · 149 days ago
- Recorded sightings
- 156
- Last seen by us
- Oct 29, 2026
- Employer says posted
- May 11, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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Job description
Meter sells networks the way utilities sell power: as something that just works. Behind that promise is a business growing fast across enterprise customers, multi-site deployments, and a partner ecosystem.
Right now, the data that runs the business is scattered across a dozen systems that don't talk to each other. This role fixes that.
Why this role matters
Every important decision at Meter — where to spend marketing dollars, which accounts to prioritize, how to forecast next quarter — is only as good as the data underneath it. Today, that data is fragmented across Salesforce, HubSpot, Stripe, ad platforms, partner systems, and product telemetry, and every team rebuilds its own version of the truth. We need one person to own the layer that turns those signals into something the company can actually run on.
What you'll do in your first six months
Ship canonical dbt models for accounts, opportunities, marketing touches, and revenue that finance, sales, and marketing all use — replacing the four versions of "ARR by segment" floating around today.
Cut the time it takes the marketing team to answer "is this channel working" from a week of manual reconciliation to a query.
Build the attribution and funnel layer that lets us actually compare the cost of acquiring a customer through partners versus paid versus outbound.
Become the person GTM leadership goes to when they don't trust a number — and the person whose work makes that question rarer over time.
What you'll do in your first year
While you're picking up quick wins, the first few months are about laying the foundation. The next are about using it.
You'll embed with finance during forecasting cycles and with marketing during budget planning. You'll be in the room when sales leadership is debating territory coverage. The business models you built in month four will be the substrate for an attribution rebuild in month nine. By the end of year one, you'll have set the standard for analytical rigor at Meter; the bar that the next five analysts we hire will be measured against.
What a typical week looks like
Monday morning you're pairing with a marketing lead on why their LinkedIn spend report doesn't match what finance recognized last quarter. Tuesday you're shipping a dbt PR that consolidates three definitions of "active customer" into one. Wednesday you're in the forecast review, watching the head of sales argue about coverage ratios, and you realize the underlying data has a fanout problem you can fix by Friday. Thursday is deeper IC work: designing the schema for a new partner data source. Friday you're reviewing a teammate's model and writing the test that catches the next regression before it ships.
What we're looking for
You've been the analytical partner inside a GTM function — not just the analyst who delivered reports to one. You've sat in pipeline reviews, argued about attribution definitions, and built dashboards that executives actually use.
You write SQL the way most people write English. You reach for window functions, CTEs, and set operations without thinking. You can read someone else's 200-line query and find the bug in ten minutes.
You think in dbt. You have opinions about staging vs. marts, when to use incremental models, and what belongs in a snapshot. You've designed schemas that survived contact with a changing business.
You've worked across Salesforce, billing systems, marketing platforms, and product data, and you understand how they're each subtly wrong in their own way.
You can take "is our marketing spend working?" and turn it into a structured analysis with a clear, defensible answer — including what you're not sure about.
You build trust before you ship models. You know the dashboard nobody uses is worse than no dashboard at all.
You have deep experience with one or more of the following: Snowflake, BigQuery, Tableau, or other modern data stacks.
Why Meter?
The internet runs the world. Every purchase you make, video call you join, it's all packets flowing through networks. But those networks haven’t changed for decades. They’re brittle, complex, and surprisingly hard to set up in an enterprise space.
We started Meter to build better networks. We had to build everything from the ground-up: designing and building our own enterprise hardware, intuitive software, and streamlined operations to deliver great outcomes for our customers. Today, we build and deploy these networks at scale. Ambitious companies and enduring institutions like Bridgewater, Lyft, Reddit, rely on Meter to keep their thousands of employees and locations online and productive.
Our bet with Meter is simple: we will all use the internet more than we do today. We believe we have the definitive networking stack in place to enable business to do so as seamlessly and reliably as any modern utility.
Compensation
The estimated base salary for this role is between $190,000 - $270,000
Additionally, this role is eligible to participate in Meter's equity plan.
By applying to this job you acknowledge that you've read and understood Meter's Job Applicant Privacy Notice.
Source details
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- Pay
Compensation The estimated base salary for this role is between $190,000 - $270,000 Additionally, this role is eligible to participate in Meter's equity plan.
- Location & working pattern
San Francisco, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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