Who gets hired
dbt Labs crossed $100 million ARR in February 2025 (PR Newswire reported) — up from $2 million four years prior — with 5,000-plus cloud customers (PR Newswire's data shows) across 43 countries (PR Newswire found). The company's own hiring choices now reveal where the modern data stack is headed.
The data team has essentially doubled in the last year, and leadership plans to keep growing it, specifically in data engineering. That expansion mirrors what dbt Labs sells: a governed collaboration layer that lets analysts self-serve on modeling and lineage while engineers focus on infrastructure, telemetry, and access controls. The internal team lives the product. Senior data analyst Chris Fiore describes the division of labor plainly: analysts own the business context and stakeholder partnership; analytics engineers and data engineers own the technical problem of moving data through the organization. Fiore came from stakeholder-facing analysis and now uses dbt's column-level lineage to trace failures before asking for help, a workflow he shares with lead data analyst Paige Berry and staff data analyst Rachael Gilbert.
On the engineering side, senior software engineer Zach Brown builds the staging layers and CI pipelines that make that self-service possible. Brown approaches the stack as a software engineer serving the data team as customer zero. He's the one who wakes up when a schema change breaks a downstream dashboard, and he's the one who writes the contracts that prevent it from happening again.
The core technical spine consists of four roles: data analyst, analytics engineer, data engineer, and senior software engineer (data infrastructure). But the board data shows a parallel hiring engine in revenue. Recent postings cluster around enterprise and major-account sales: Enterprise Sales Directors for Australia, the Pacific Northwest, North Central, and Boston; Majors Sales Directors for the Bay Area and Boston; a Global Alliance Lead. The split tells a story: dbt Labs is scaling a product-led motion that still requires high-touch enterprise selling, and it's doing both from a remote-first footprint.
Geography shapes the team map. The company maintains offices in Philadelphia, New York, Austin, and Dublin but has concentrated APAC expansion through in-market hires in Japan, Australia, and New Zealand. The domain-based structure dbt Labs advocates for its customers (centralized platform, embedded domain analysts) appears in the model it runs internally. Logan Cochran, a data analyst at the company, said the team was historically small and is now growing fast enough that role boundaries are still settling. That fluidity shows up in the research: analysts at dbt Labs write SQL, trace lineage, and occasionally dip into Python with AI assistance; engineers build the catalog, the CI gates, and the contracts that make those dips safe.
What unifies the technical hires is fluency in the dbt paradigm: models as code, tests as contracts, lineage as a daily habit. The company hires people who have felt the pain of broken handoffs — whether from the analyst side waiting on a ticket, or the engineer side drowning in requests — and want to build the guardrails that make governed collaboration the path of least resistance.
Sales hires follow a different but adjacent logic. The Enterprise and Majors Director roles demand territory ownership and complex-cycle experience, but the product they're selling is the very workflow the internal data team runs. A sales director who understands why a staff analyst cares about column-level lineage can credibly pitch a VP of Data. That alignment — product, internal team, and go-to-market speaking the same language — is the hiring signal worth watching.
Pay
dbt Labs compensates at the upper end of the SaaS market, with total packages that sit alongside mid-range FAANG offers. The clearest picture comes from the company's own job postings, which show a salary band of $146k–$371k (median $290k) across 13 salaried roles posted recently, Zero G Talent's job board shows. Those listings are heavily weighted toward sales leadership:
| Role | Location | Salary Band |
|---|---|---|
| Enterprise Sales Director | Australia | 400k–500k AUD |
| Majors Sales Director | Boston | $300k–$380k (Zero G Talent's job board lists) |
| Majors Sales Director | Bay Area | $300k–$375k (according to Zero G Talent's job board) |
| Enterprise Sales Director | Pacific Northwest | $260k–$330k |
| Enterprise Sales Director | North Central | $238k–$320k |
| Global Alliance Lead | Remote | $239k–$290k |
All are remote-eligible, reflecting the company's distributed-first model.
Third-party aggregates confirm the spread. Levels.fyi, drawing on 212 reported data points as of August 2026, puts the median total compensation at $193k, with a floor of $59k for a recruiter in India and a ceiling of $500k for a U.S.-based human-resources role. Glassdoor shows a similar volume (212 salaries across 114 titles) posted anonymously by current and former employees.
For product management, the most granular public breakdown comes from Big Tech Salary Blog's 2026 analysis of dbt's internal compensation grid:
| Level | Base | Bonus (10–15%) | Equity (annual) | Total Comp (est.) |
|---|---|---|---|---|
| L3 | $120k–$140k | $12k–$21k | $30k–$40k | ~$170k |
| L4 | $150k–$170k | $15k–$26k | $60k–$80k | ~$250k |
| L5 | $190k–$210k | $19k–$32k | $100k–$130k | ~$330k |
| L6 | $240k–$260k | $24k–$39k | $150k–$180k | ~$420k |
The blog notes the grid updates annually using public market data from Levels.fyi and peer-company filings. Bonus rates run modest compared with high-growth SaaS peers that often pay 20% or more, but equity grants widen the gap, placing dbt in the upper quartile of SaaS and on par with mid-range FAANG packages.
Equity follows a standard four-year RSU vest with a one-year cliff (25%) and monthly vesting thereafter (2.08% per month for years two through four), per Remotivated's summary. An employee stock purchase plan is also available. A caution: Private Pulse flags that dbt Labs has merged into another entity, so equity valuations reflect pre-merger pricing; candidates should verify current conversion terms.
Experience-based bands from a practitioner-focused YouTube walkthrough (August 2026) align broadly: entry level $75k–$90k, mid-level (2–3 years) $90k–$110k, senior (5+ years) $110k+, with outlier roles reaching $200k. The same source emphasizes that base pay is only the floor (bonuses, RSUs, and 401(k) matching sit on top) and that communication ability, industry (finance, healthcare, tech pay premiums), and location (San Francisco/New York vs. smaller markets) move the needle more than raw technical skill.
Negotiation leverage exists. Big Tech Salary Blog confirms base and equity can be negotiated separately, and advises building a total-comp model that weights equity at 60% for L5/L6 roles to capture real upside. Candidates who request level-specific bonus multipliers documented in hiring-committee notes, or ask for vesting-acceleration clauses tied to change-of-control events, signal market awareness that recruiters respect.
dbt Labs pays like a late-stage SaaS company that knows it competes for the same talent as the cloud hyperscalers. Cash is competitive but not the headline; the equity component, tied to a $500M–$1B revenue trajectory and projected 2–3× upside over the vesting period, is where the offer differentiates.
The interview loop
The dbt Labs interview loop runs three to four weeks from first contact to offer, moving fast enough that candidates have little time to cram between rounds. Most people report four to six touchpoints total, though the exact sequence shifts depending on whether you're targeting analytics engineering, data platform, or product engineering. The shape stays consistent: a recruiter screen, a live technical pairing session, a code-review-and-behavioral conversation, then a virtual onsite that bundles three to four back-to-back rounds, and occasionally a final leadership chat.
The recruiter screen is 30 minutes, often triggered by a LinkedIn message. It covers motivation, rough level, compensation expectations, and whether you actually understand what dbt does: the ingestion-to-transformation-to-serving path that the Fivetran merger now unifies under one roof. Candidates who can't articulate where their work would sit along that path tend to stall here.
The technical pairing round is the one that matters. Sixty minutes, live, debugging and optimizing an existing function or model rather than writing from scratch. The interviewer sits beside you in the editor (CoderPad or a shared IDE) and expects you to talk through every hypothesis. "Sitting in silence for four minutes while you think reads worse here than a wrong guess you explain out loud," a senior engineer on the loop said. They're scoring how you read unfamiliar code, whether you write a failing test before touching logic, and whether working with you all day would be pleasant. This round is where offers are won and lost.
Next comes a 45-to-60-minute code review and behavioral hybrid. You'll walk through a diff or a past project, and the interviewer probes judgment on correctness, readability, and the tradeoffs you made. Vague answers hurt; they want the metric you moved, the incident you caused and fixed, the decision you later regretted.
The virtual onsite strings together three to four rounds in a single block:
- Coding Round 1 (DSA): Algorithmic problem-solving with emphasis on efficiency, edge cases, and clean code. Graph problems dominate (topological sort, cycle detection, dependency resolution) because dbt's entire model dependency system is a Directed Acyclic Graph.
- Coding Round 2 (Practical): Applied work: building a small utility, traversing a graph, or managing dependencies in a way that mirrors dbt's DAG architecture.
- System Design: A virtual whiteboard session grounded in the product. Recent prompts include designing a dbt Cloud orchestration system that handles scheduling, retries, and dependency-aware execution, or a metrics layer that compiles to SQL across multiple warehouses. The bar is pragmatic engineering, not distributed-systems trivia.
- Past-Project Deep Dive: A dedicated 45-to-60-minute walkthrough of one complex project you owned. Unlike most companies that fold this into behavioral rounds, dbt Labs gives it a full slot. They want to know why you made each technical choice and what you'd do differently.
- Behavioral Round: Focused on collaboration, values alignment, and what dbt Labs calls "developer empathy": the ability to build tools that other technical practitioners genuinely enjoy using. Expect questions about making features easier to debug or document for an analytics engineer, handling ambiguous ownership, and helping people outside your team use your work.
A final 30-to-45-minute conversation with a hiring manager or executive sometimes closes the loop, checking values fit and product thinking.
What gets candidates through? SQL is treated as a first-class engineering skill, not an afterthought. Struggling with window functions, recursive CTEs, or query optimization tradeoffs is often a hard fail regardless of Python or Go strength. For dbt-adjacent roles, interviewers assume you've shipped real dbt projects — not just read the docs. They check for scars: materialization choices (view vs. table vs. incremental vs. ephemeral), incremental model failure modes (double-counting after backfills, unique_key config, append vs. merge strategies, lookback windows), snapshot Type 2 history with dbt_valid_from/dbt_valid_to, test strategy (built-in vs. custom generic vs. singular), and why ref() builds the DAG while hardcoded table names throw it away.
Knowing the dbt Fusion engine (the Rust rewrite of the parser and compiler from the SDF acquisition, shipped in dbt Core v2.0 under Apache 2.0) signals you're tracking where the tool is going. You don't need production experience with it, but you should explain why a SQL-aware compiler matters for large projects.
Because the company is fully remote and writing-focused, evidence of clear async communication carries weight. The dbt community (Slack, Coalesce, thousands of open-source contributors) is a growth engine, so candidates who can write and teach stand out. Bring three or four behavioral stories with concrete stakes and outcomes, structured with the STAR principle, and be ready to say what you'd do differently. The fast loop leaves little room to improvise.
Where the work happens
dbt Labs operates as a remote-first company with four physical offices that function as collaboration anchors rather than daily mandates. The company's BuiltIn profile states it directly: "At our 100% remote company, employees have the flexibility to work from wherever they work best. We host annual retreats and bi-annual team gatherings." That philosophy shapes how the offices are used — and who uses them.
Philadelphia: HQ and product center
The headquarters sits at 915 Spring Garden Street in Philadelphia's Callowhill neighborhood. Per The Buildout, the space houses R&D and sales/support functions. Founded in 2016 as Fishtown Analytics by Tristan Handy, Drew Banin, and Connor McArthur (former RJMetrics colleagues), the company rebranded to dbt Labs in 2021 after the open-source dbt project gained traction. Philadelphia remains the gravitational center for product and engineering, with 207 product and tech employees reported across the organization as of the latest BuiltIn snapshot.
New York: go-to-market hub
A second U.S. office occupies 900 Broadway, Suite 402, in Manhattan's Flatiron district. The Silicon Republic profile from March 2024 noted a "new office opening in New York" as part of leadership expansion that brought on a president/COO (Brandon Sweeney), CTO, and CRO. The New York location supports go-to-market teams and provides a northeast corridor hub for client-facing roles.
Austin: small by design
Austin joined the map in July 2024 when the Austin Business Journal reported a lease signed downtown, "one of the few new ones signed recently by tech executives downtown," per the outlet. The space is described as small, signaling intentional growth rather than speculative expansion. The PR Newswire announcement from February 2025 listed Austin among "new offices" alongside Dublin, confirming it as an active site.
Dublin: Europe launchpad
Dublin marks dbt Labs' first European hub, opened in early 2024. Silicon Republic reported that the office "will be the start-up's main hub on the continent, particularly for its EMEA sales team." CEO Tristan Handy emphasized language capability as a strategic driver: "As we look to scale into and across Europe, obviously language matters as we start to capture key leading customers in each of the countries that we look to go build direct operations in and we're going to do that based out of Dublin here." He added a longer-term vision: "Over time, I hope we can ultimately export some teams where people want to grow their careers if they want to move back into their different countries where they have language proficiency and fluency. We'd love to support that."
Remote by default
The first-party board data reinforces the remote-first reality. Recent postings list locations as "US - Remote," "US East - Remote," "US Central - Remote," and "Australia - Remote", not tied to any office. Roles span enterprise sales directors across U.S. regions (Pacific Northwest, North Central, Bay Area, Boston) and a Global Alliance Lead, all designated remote.
That flexibility extends to APAC. The February 2025 PR Newswire release noted "in-market employees in Japan are now joining dbt Labs teams in Australia and New Zealand" and flagged "concentrating expansion efforts in APAC." No dedicated APAC office appears in the current four-office count, suggesting the region operates through distributed teams for now.
What the offices do
The offices serve three purposes: onboarding cohorts, deep collaboration sprints, and customer-facing events. Annual retreats and bi-annual team gatherings (called out explicitly on the company's BuiltIn page) bring distributed employees together for planning and relationship-building that async work struggles to replicate. Sales teams in Dublin and New York use proximity to prospects; R&D in Philadelphia uses the space for hardware-heavy work and whiteboarding sessions that benefit from shared physical context.
The model reflects a company that crossed $100M ARR in February 2025 with 5,000+ cloud customers across 43 countries. Physical footprint follows revenue concentration: Philadelphia for product, New York and Dublin for enterprise sales, Austin as a growing talent magnet. Everyone else works from where they're productive — and the job postings confirm that's by design.
Who thrives
dbt Labs hires people who treat transparency as a default operating mode rather than a compliance exercise. The company's values page states it plainly: transparency is a north star, and acting transparently serves the long-term mission. That shows up in salary bands published internally and posted externally, in career ladders visible to every employee, and in a leadership model that asks leaders to "lean into debate and work to disconfirm our own beliefs," finding the most credible people who disagree and trying to understand their reasoning. Disagreement in public is expected; commitment after a decision is required.
The culture rewards a specific kind of humility. "We are humble" appears alongside "we work hard and go home" and "we are human" on the same values list, and the combination shapes daily behavior. Employees describe a workplace where admitting uncertainty carries less penalty than pretending to know, where the goal is value creation rather than value capture, and where profits are treated as a tool for the mission, not the mission itself. That orientation attracts people who have watched other companies optimize for short-term metrics and want to build something that compounds.
Internal mobility data reinforces the pattern. In 2021, 10 percent of roles were filled by existing team members moving up the stack; the target for 2022 was 15 percent. The Foundry Program, launched in 2021, formalizes this by offering paid apprenticeships with benefits to software and analytics engineers from non-traditional backgrounds. Partnerships with bootcamps serving groups historically excluded from tech followed in 2022. Over half the team participates in one of three DEI sub-committees, and the company reports that 33 percent of employees are caregivers while 10 percent have a disability — figures the company publishes voluntarily. A Conscientious Objection policy lets individuals opt out of projects that conflict with personal values, and a Company Stance policy prevents taking on customers the majority of the team would object to on ethical grounds.
Glassdoor reviews average 3.3 out of 5 stars across 91 reviews, and Built In analysis notes scaling-related strains that include shifting priorities, heavier workloads, and uneven transparency in practice. People who thrive here tend to be comfortable with ambiguity, willing to debate openly, and able to set boundaries — "work hard and go home" is a value, not a slogan. The abundance mindset the company articulates ("we believe that all team members should seek to replace themselves on an ongoing basis by building processes, technology, and documentation that obviate their existing work") selects for builders who document as they go and treat knowledge transfer as part of the job.
Leaders only slow down for one-way-door decisions. For everything else, the bias is toward calculated risk and fast learning. That means the people who stay are the ones who can operate without perfect information, who default to open source and thinking in public, and who see the community of 25,000+ practitioners and 50+ global meetups as their extended team.
The same analysts who once waited on engineering tickets now ship models that engineers trust without review. The engineers who once drowned in requests now build the guardrails that make self-service safe. dbt Labs hired for that handoff — and the org chart proves it worked.
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