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Cartesia

Analytics Engineer

Location*HQ - San Francisco, CA
Work modeon-site
Typefull-time
DepartmentEngineering
EquityIncluded
Company size11+ people
First seen3h ago
Last seen3h ago
About Cartesia
Our mission is to architect AI that learns from and interacts with the world like humans do.
We’re pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.
We’re funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We’re fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world’s foremost experts in AI.
About the Role
We’re hiring an Analytics Engineer to build and own Cartesia’s company-wide source of truth. You’ll bring together product, billing, CRM, marketing, and operational data into reliable models and shared metric definitions that teams can trust.
This is an early, foundational data hire. You’ll fix urgent correctness issues, strengthen the warehouse and transformation layer, and create the first trusted dashboards for Product, GTM, Growth, RevOps, and leadership. The goal is not simply to answer questions—it is to build the systems, models, and standards that let the company answer them consistently.
Your Impact
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Own the path from source systems to canonical datasets, metrics, and dashboards.
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Identify and fix data-quality issues across pipelines, models, definitions, and reporting surfaces.
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Build and maintain reliable warehouse models using SQL and dbt or equivalent tooling.
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Establish clear metric definitions, tests, lineage, freshness monitoring, documentation, and ownership.
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Partner closely with Product, Engineering, RevOps, Growth, and GTM to translate business concepts into durable data models.
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Create trusted dashboards for core company metrics such as activation, usage, billing, customer health, and marketing performance.
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Make common data questions self-serve while ensuring dashboards reuse canonical logic rather than duplicating it.
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Audit the existing data stack and recommend pragmatic improvements or overhauls to ETL and analytics tooling where needed.
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Educate the company on how to use the source of truth and how new metrics and dashboards should be created.
What You Bring
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5+ years in analytics engineering, data engineering, or a technically rigorous analytics role, ideally at a B2B SaaS or developer-tools company.
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Expert SQL and strong warehouse modeling fundamentals, including dimensional modeling, historization, and identity resolution.
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Production experience with dbt or similar transformation tooling, plus testing, orchestration, monitoring, lineage, and documentation.
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A track record of turning fragmented data and competing definitions into canonical, reusable models.
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Experience working across product, billing, CRM, and marketing data; self-serve funnel experience is especially valuable.
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Strong judgment about when a problem belongs in a source system, pipeline, warehouse model, semantic layer, or dashboard.
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The ability to investigate discrepancies end-to-end and prevent them from recurring—not just patch the final report.
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Strong stakeholder instincts and the ability to make ambiguous business concepts precise.
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A practical, low-ego approach: willing to fix urgent issues while building toward a durable foundation.
Nice-To-Haves
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Experience as an early or founding member of a data function.
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Experience with full-funnel growth analytics, attribution, channel ROI, CRM, billing, or self-serve conversion.
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Experience building self-serve data workflows or using LLM-powered analytics tooling.
Not Required
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Machine learning, predictive modeling, or traditional data science experience. This is an analytics engineering role focused on trustworthy systems and source-of-truth ownership.
Legal
Note: Cartesia participates in E-Verify and will provide the federal government with Form I-9 information to confirm employment eligibility after hire.
More Details
🏢 In-office policy: We’re an in-person team based out of offices in 🇺🇸 San Francisco, 🇬🇧 London and 🇮🇳 Bangalore. We love being in the office, hanging out together, and learning from each other every day.
🌎 Visa sponsorship: We provide visa sponsorship support and assess each circumstance on a case-by-case basis. However, visa sponsorship is dependent on many factors, including the role you are applying for, and the location you are going to be based, and so we can’t always guarantee success. Your Recruiter will work with you to understand your visa sponsorship needs from the first call.
🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way.
🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.
Our Benefits (US Employees Only)
💰 Compensation Competitive base salary alongside attractive equity package.
🩺 Health Insurance Fully covered medical insurance along with dental and vision for you and your family.
🧑‍🧑‍🧒‍🧒 Parental Leave 9 weeks paternity & 12 weeks maternity leave
🏦 401(k)
🚆 Commuter Allowance A monthly stipend to help you get to and from the office.
🏖️ Flexible PTO Take as much time as you need to recharge your batteries.
🍲 Meals & Snacks Lunch, dinner and plenty of snacks, provided daily.
🦖 Your own personal Yoshi
Our Commitment to Equal Opportunity
Cartesia is an equal opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, genetic information, or any other legally protected status.
More roles at Cartesia
Engineering Manager, ProductExecutive Business PartnerEngineering Manager, PlatformProduct and Research Operations Manager, VoicesScaled Customer Success Manager
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