Analytics Engineer

Cartesia

$120K — $145K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in analytics engineering, data engineering, or a similar analytics role, ideally in a B2B SaaS environment.
  • Expertise in SQL and sound warehouse modeling principles including dimensional modeling.
  • Hands-on experience with dbt or equivalent ETL/analytics tooling, including monitoring and testing.
  • Proven ability to create canonical data models from fragmented datasets.
  • Experience integrating product, billing, CRM, and marketing data for analytics purposes.
  • Strong analytical skills to investigate data discrepancies and ensure data integrity.
  • Ability to translate ambiguous business concepts into clear data models and metrics.

Responsibilities

  • Lead the development of standardized datasets, metrics, and dashboards from source systems.
  • Resolve data quality issues by auditing pipelines and reporting surfaces.
  • Construct and manage robust warehouse models using SQL and dbt.
  • Define clear metric definitions and ensure accurate documentation and monitoring.
  • Collaborate with various teams to align business requirements with data structures.
  • Create reliable dashboards for key metrics like customer health and marketing performance.
  • Promote self-service analytics by centralizing common data queries and logic.

Benefits

  • Fully covered medical, dental, and vision insurance for employees and their families.
  • 9 weeks of paternity and 12 weeks of maternity leave.
  • 401(k) retirement plan options available.
  • Monthly commuter allowance for transportation costs.
  • Generous flexible PTO policy allowing for ample time off.
  • Daily meals and snacks provided at the office.
Full Job Description
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
  • Own the path from source systems to canonical datasets, metrics, and dashboards.
  • Identify and fix data-quality issues across pipelines, models, definitions, and reporting surfaces.
  • Build and maintain reliable warehouse models using SQL and dbt or equivalent tooling.
  • Establish clear metric definitions, tests, lineage, freshness monitoring, documentation, and ownership.
  • Partner closely with Product, Engineering, RevOps, Growth, and GTM to translate business concepts into durable data models.
  • Create trusted dashboards for core company metrics such as activation, usage, billing, customer health, and marketing performance.
  • Make common data questions self-serve while ensuring dashboards reuse canonical logic rather than duplicating it.
  • Audit the existing data stack and recommend pragmatic improvements or overhauls to ETL and analytics tooling where needed.
  • Educate the company on how to use the source of truth and how new metrics and dashboards should be created.
What You Bring
  • 5+ years in analytics engineering, data engineering, or a technically rigorous analytics role, ideally at a B2B SaaS or developer-tools company.
  • Expert SQL and strong warehouse modeling fundamentals, including dimensional modeling, historization, and identity resolution.
  • Production experience with dbt or similar transformation tooling, plus testing, orchestration, monitoring, lineage, and documentation.
  • A track record of turning fragmented data and competing definitions into canonical, reusable models.
  • Experience working across product, billing, CRM, and marketing data; self-serve funnel experience is especially valuable.
  • Strong judgment about when a problem belongs in a source system, pipeline, warehouse model, semantic layer, or dashboard.
  • The ability to investigate discrepancies end-to-end and prevent them from recurring-not just patch the final report.
  • Strong stakeholder instincts and the ability to make ambiguous business concepts precise.
  • A practical, low-ego approach: willing to fix urgent issues while building toward a durable foundation.
Nice-To-Haves
  • Experience as an early or founding member of a data function.
  • Experience with full-funnel growth analytics, attribution, channel ROI, CRM, billing, or self-serve conversion.
  • Experience building self-serve data workflows or using LLM-powered analytics tooling.
Not Required
  • Machine learning, predictive modeling, or traditional data science experience. This is an analytics engineering role focused on trustworthy systems and source-of-truth ownership.


More Details

In-office policy: We're an in-person team based out of offices in US San Francisco, GB London and I🇳 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

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