Senior Analytics Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Analytics Engineer based in the United States.

As a Senior Analytics Engineer, you will own the data models and measurement infrastructure that power go-to-market decisions across self-serve and sales-led funnels. You will turn complex product, CRM, marketing, and spend data into trusted metrics that help teams understand growth and improve performance. The role combines hands-on analytics engineering with strategic partnership across Marketing, Sales, Revenue Operations, Product, and Finance. You will build reliable data models, semantic layers, attribution frameworks, and unit economics reporting in a modern cloud data environment. You’ll work with imperfect real-world data and be expected to investigate problems, define the right questions, and create practical solutions. As an individual contributor, you’ll have significant influence over how go-to-market data is modeled, measured, and used across the organization.

• Own and continuously improve the go-to-market data model, establishing consistent definitions for accounts, activated workspaces, pipeline, and other critical business metrics.
• Build production-grade analytics models in dbt with appropriate testing, documentation, CI, version control, and deployment practices.
• Model the complete self-serve funnel, from first website interaction through signup, activation, paid conversion, and expansion across multiple products.
• Develop comparable cohorts and funnel reporting that clearly identifies conversion drop-offs and opportunities for improvement.
• Model the sales funnel from acquisition source through MQL, SQL, pipeline, and closed-won, using real-world Salesforce data and accounting for data-quality challenges.
• Build and maintain attribution models spanning first-touch, last-touch, and multi-touch approaches, clearly documenting assumptions and methodologies.
• Develop unit economics reporting covering CAC, payback, LTV/CAC, campaign ROI, event ROI, and comparisons between self-serve and sales-assisted motions.
• Source and integrate marketing and campaign spend data that may not yet be available in existing reporting systems.
• Build and maintain a scalable reporting and semantic layer in Omni, Looker, or a comparable analytics platform so go-to-market teams can answer questions independently.
• Support recurring go-to-market operating rhythms, including pipeline reviews, weekly funnel meetings, and executive or board reporting.
• Partner directly with Marketing, Sales, Revenue Operations, Product, and Growth leadership to translate business questions into meaningful analysis and actionable metrics.
• Proactively identify underlying data issues, inconsistencies, and gaps, and determine how they should be measured or resolved rather than simply waiting for predefined requirements.
• Work with product analytics, CRM, marketing automation, and customer data systems to ensure reliable data flows and usable metrics.
• Use Python for API integrations, spend-data ingestion, enrichment, and analytical tasks where SQL is not the right tool.
• Leverage AI-native development practices and identify opportunities to make analytics engineering workflows faster, more reliable, and more efficient.

Requirements:

• 4+ years of experience building and maintaining analytics models in dbt on a cloud data warehouse, with ownership of production workflows, testing, CI, and version control.
• Strong SQL skills and practical Python experience for API pulls, data ingestion, enrichment, and specialized analytical tasks.
• Experience building and maintaining a semantic layer in Omni, Looker, or a comparable analytics platform, with an emphasis on creating reusable metrics for business users rather than simply building dashboards.
• Direct experience partnering with go-to-market teams on funnel conversion, attribution, unit economics, CAC, payback, ROI, and related growth metrics.
• Hands-on experience working with CRM data from Salesforce, HubSpot, or comparable systems.
• Familiarity with go-to-market technology ecosystems including Salesforce, Amplitude, Segment, HubSpot, and related platforms.
• Experience in a product-led, self-serve, or usage-based business, with an understanding of activation, trials, PQLs, product usage, and conversion.
• Engineering or data-focused background with the ability to write production code, understand existing codebases, and deploy owned work.
• Strong understanding of data modeling, metric definitions, data quality, and analytical infrastructure.
• Comfort working with imperfect or inconsistent data and the persistence to investigate the underlying causes rather than relying on idealized schemas.
• Strong business judgment and communication skills, with the ability to turn open-ended questions into clear analytical approaches and actionable recommendations.
• Ability to work independently as a senior individual contributor while influencing how teams use and understand go-to-market data.
• Comfort with AI-native development and a proactive approach to using AI tools to improve engineering productivity and analytical workflows.
• Experience with product analytics platforms, particularly Amplitude, is a plus.
• Experience working with developer tools, open-source products, or community-driven growth models is a plus.

Benefits:

• Competitive location-based base salary:
  • $173,000–$222,000 for the San Francisco Bay Area and NYC Metro.
  • $162,000–$201,000 for Washington, D.C., Boston, Los Angeles Metro, and Seattle.
  • $154,000–$200,000 for Denver, Chicago, Atlanta, and other U.S. metropolitan areas.
  • Equity stock options.
  • 401(k) plan with a 5% company match, with immediate vesting.
  • Unlimited paid time off.
  • Medical, dental, and vision insurance.
  • Generous parental leave.
  • Life insurance and disability benefits.
  • $800 per month remote-work stipend.
  • Remote-first, flexible work environment.
  • Opportunity to work on modern data, analytics, automation, and AI infrastructure.
  • Significant autonomy and ownership as a senior individual contributor.
  • Opportunity to influence how go-to-market teams measure growth, performance, attribution, and economics.
  • Collaborative, high-performance culture that values ownership, thoughtful communication, continuous learning, and meaningful impact.
  • Inclusive environment designed to provide individuals and teams with access, opportunity, and the ability to contribute authentically.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

#LI-CL1