Analytics Engineer
Who we are: We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens.
What this role actually needs.
Analytics Engineer at Sardine in North America. UpJobz keeps this listing high-signal for applicants targeting serious high-tech roles across the United States, Canada, and Mexico. Who we are: We are a leader in fraud prevention and AML compliance. Our platform uses device intelligence, behavior biometrics, machine learning, and AI to stop fraud before it happens.
Day-to-day expectations
A clear list of the work this role is designed to cover.
- Build, refine and own Sardine’s internal data infrastructure — integrating CRM, marketing, product, finance, and operational systems into a cohesive, well-modeled data warehouse.
- Partner closely with the Security and Infrastructure teams on the security architecture of our internal data warehouse to ensure robust data protection, access controls, and compliance standards are upheld.
- Design, improve, implement, and own ETL/ELT pipelines to ensure clean, reliable, and scalable data flows across the organization.
- Partner with data, engineering, revenue/business operations, and executive stakeholders to define and track KPIs, ensuring business decisions are grounded in data.
- Serve as the connective tissue between Revenue Operations, Business Operations, and Product/Eng — translating complex requirements into elegant data solutions.
- Champion data quality and governance, ensuring our insights are consistent, trustworthy, and well-documented.
What a strong candidate brings
This keeps the job page specific, readable, and easier to match.
- Champion data quality and governance, ensuring our insights are consistent, trustworthy, and well-documented.
- Develop dashboards and analytics, when applicable, that provide key insights for executive leadership, GTM, Product, and Finance.
- Be proactive and scrappy — spotting opportunities to automate, optimize, and drive better visibility across teams.
- 5+ years of experience in data engineering, analytics engineering, or business intelligence, ideally supporting GTM or business functions.
- Proven ability to manage data integrations across various platforms such as Salesforce, Hubspot, BigQuery/Snowflake, Amplitude, Sigma, Clay, etc.
- Experience with Python for automation and API integrations.
Why people would want this job
Benefits help searchers understand whether the role is a real fit before they apply.
- Generous compensation in cash and equity
- Early exercise for all options, including pre-vested
- Work from anywhere: Remote-first Culture
- Flexible paid time off and Year-end break
- Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific
- 4% matching in 401k / RRSP - US and Canada specific
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Next moves
- Tailor your resume around ai and llm instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to analytics engineer is a high-signal remote role in north america, and it is most realistic for united states residents.
- Open the role quickly if it fits and bookmark three similar jobs before you leave the page.
Interview themes
Watchouts
- $160K - $190K is visible, so calibrate your application around the posted range.
- Use united states residents as part of your positioning so the recruiter does not have to infer it.
- Lead with distributed collaboration, async delivery, and timezone discipline.
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