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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Klaviyo, Inc. - **Location:** Boston, MA, United States - **Experience:** Expert - **Salary:** $112,000.0 - $168,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, BigQuery, Business Systems, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Mart, Data Systems, Data Warehousing, Database Testing, Python (Programming Language), Salesforce.Com, SQL Databases, Systems Integration, Usage Analysis, Snowflake, Zapier, Functional Programming, Terraform, Data Pipelines - **Published:** July 28, 2026 - **Apply:** https://www.dice.com/job-detail/61b057d3-6770-4256-833e-253e01ffe0ae ## About the Role * 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. ## Description 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 ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [HR ROBO SAPIENS: Decoding AI Agents and Workflow Automation for Modern Recruitment](https://www.wearedevelopers.com/videos/1470-hr-robo-sapiens-decoding-ai-agents-and-workflow-automation-for-modern-recruitment) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Making Data Warehouses fast. 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