Senior Analytics Engineer

Klaviyo•Boston, MA

10h•Hybrid

About The Position

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. 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. Please note that this is a hybrid role that requires 3 days/week in our Boston office. Fully remote candidates will not be considered at this time.

Requirements

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 Haves

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)

Responsibilities

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
Build and maintain production-grade dbt models in Snowflake
Own ingestion from systems like Salesforce, ERP, and product data sources
Push high-value data models into downstream tools and workflows
Implement testing frameworks, monitoring, and documentation to ensure trust and compliance
Work closely with Sales Ops, Product Managers, Engineering, Finance, and GTM teams
Maintain dbt codebase, enforce best practices, and ensure scalability
Contribute to Airflow, Terraform, AWS, and other platform tools as needed