Analytics Engineer

We’re looking for a Senior Analytics Engineer to own end-to-end data pipelines and modeling across GTM (Sales) and Product domains. You’ll build and maintain the source of truth for operational and product data, enabling leadership, analysts, and product teams to answer complex questions with confidence. This role combines deep technical execution with high-impact business partnership, requiring you to translate ambiguous needs into scalable data products. You will operate as a trusted, embedded partner to stakeholders while leveraging the broader Data Engineering organization’s standards, tooling, and best practices. You’ll help build the foundation that powers everything from forecasting and compensation to product insights and experimentation.

How You’ll Make a Difference

• Own and deliver end-to-end data pipelines and models that power Sales and Product analytics
• Build curated, governed data marts that enable fast, reliable decision-making
• Design dimensional data models (dbt) for core entities such as accounts, pipeline, performance, and product usage
• Partner with Sales, Product, and Analytics teams to create holistic views of the customer and product lifecycle
• Raise the bar on data quality, testing, monitoring, and documentation
• Enable reverse ETL workflows to operationalize insights into business systems
• Act as a data ambassador across Product, Engineering, BI, and Legal, ensuring alignment on data contracts and governance
• Lead and mentor others through design reviews, best practices, and technical guidance
• Evolve internal tooling and infrastructure to improve developer and analyst productivity

What You’ll Do

• Data Modeling & Pipelines: Build and maintain production-grade dbt models in Snowflake
• Integrations & Ingestion: Own ingestion from systems like Salesforce, ERP, and product data sources
• Reverse ETL: Push high-value data models into downstream tools and workflows
• Data Quality & Governance: Implement testing frameworks, monitoring, and documentation to ensure trust and compliance
• Cross-Functional Partnership: Work closely with Sales Ops, Product Managers, Engineering, Finance, and GTM teams
• Repository Stewardship: Maintain dbt codebase, enforce best practices, and ensure scalability
• Tooling & Infrastructure: Contribute to Airflow, Terraform, AWS, and other platform tools as needed

• 5+ years of experience in analytics or data engineering in a modern data stack (Snowflake, BigQuery, or Redshift)
• Strong expertise in SQL and dbt, with a focus on building scalable, production-grade data models
• Proficiency in Python (or similar) for orchestration or tooling
• Experience owning end-to-end data workflows, from ingestion to business impact
• Ability to translate ambiguous business needs into structured data solutions
• Strong communication skills with the ability to partner with non-technical stakeholders
• Experience implementing data testing, monitoring, and governance frameworks
• Proven ability to lead cross-functional projects with minimal guidance

Nice to Have

• Experience with Sales Operations, compensation, or GTM analytics
• Familiarity with reverse ETL tools and workflows
• Experience with Airflow, Fivetran, Workato, or similar tools
• AWS experience (S3, EC2, Lambda) and infrastructure-as-code (Terraform)
• Exposure to experimentation frameworks or product analytics systems
• Experience with data privacy controls (masking, role-based access, compliance)

Massachusetts Applicants:It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Our salary range reflects the cost of labor across various U.S. geographic markets. The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations. The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.

In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility.

Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.

Base Pay Range For US Locations:

$112,000-$168,000 USD

This role may require up to 10% travel for purposes such as new hire onboarding, client or partner work if applicable, team meetings, and industry events. Travel is coordinated in advance.

Get to Know Klaviyo

We’re Klaviyo (pronounced clay-vee-oh). We empower creators to own their destiny by making first-party data accessible and actionable like never before. We see limitless potential for the technology we’re developing to nurture personalized experiences in ecommerce and beyond. To reach our goals, we need our own crew of remarkable creators-ambitious and collaborative teammates who stay focused on our north star: delighting our customers. If you’re ready to do the best work of your career, where you’ll be welcomed as your whole self from day one and supported with generous benefits, we hope you’ll join us.

AI fluency at Klaviyo includes responsible use of AI (including privacy, security, bias awareness, and human-in-the-loop). We provide accommodations as needed.

Data is at the heart of every decision at Klaviyo. Our Analytics Engineering team sits within a hub-and-spoke model, partnering closely with Go-To-Market (GTM), Product, Engineering, and Business Intelligence teams to build scalable, trusted data systems. You’ll work at the intersection of business and engineering, owning core data models, enabling self-service analytics, and ensuring our data ecosystem is reliable, scalable, and compliant.