Senior Analytics Engineer
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements.
What this role actually needs.
At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. Responsibilities: - 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 Requirements: - 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 Company context: Klaviyo is the public marketing automation and CDP company powering email, SMS, and AI personalization for ecommerce.
Day-to-day expectations
Klaviyo lists these responsibilities for the Senior Analytics Engineer role.
- 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
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 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
Why this listing is more than a copied job post.
Senior Analytics Engineer is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
United States tech market
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Compensation read
The employer source does not expose a reliable salary range, so candidates should ask for compensation early instead of waiting until late-stage interviews.
Work authorization read
Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
On-site roles in Boston should be compared against commute, local salary bands, and nearby employer demand.
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- Compensation is hidden, so get range clarity in the first recruiter conversation.
- Use open to tn, h-1b, and opt candidates already in the united states as part of your positioning so the recruiter does not have to infer it.
- Show concrete examples of succeeding in on-site environments.
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Apply through the employer source
Open the source listing from klaviyo.com, confirm the role is still active, then apply on the employer or ATS page.
Source: klaviyo.com · Source ID: 7718472003 · Confidence: 88/100 · Last checked: May 7, 2026
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