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. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit careers.klaviyo.com to see how we empower creators to own their own destiny.

Klaviyo is looking for a Senior Analytics Engineer to join our growing R&D team. Data is core to who we are as a company, and you will play a pivotal role in data engineering to ensure that Product Analytics is developing datasets in a scalable, compliant, and efficient manner. Our team works closely with product managers and engineers to best serve the needs of customers within specific product areas. 

Klaviyo is located in the heart of downtown Boston. We build software that helps tens of thousands of businesses have more relevant and personal relationships with billions of consumers. We are a product-driven company and over invest in making beautiful, efficient, and fast workflows that help our customers accomplish what was previously unimaginable. We push each other to move out of our comfort zone, learn new technologies, and work hard to ensure each day is better than the last.

The ideal candidate is intellectually curious, proactive in seeking solutions to challenging problems, and highly focused on delighting our customers. This person will also act as the product-data ambassador for Business Intelligence, Engineering, and Legal. The Analytics Engineer will streamline data warehousing processes and practices, while also extending the trusted data sources by partnering with other analytics and engineering teams across Klaviyo. 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. 

How you’ll make a difference

• End‑to‑end data: Design, build, and own production‑grade dbt models that power key Product metrics—complete with testing and documentation. You will treat datasets as products, not tasks.
• Roadmap leadership: Scope and deliver large-scale, cross-functional projects with self-direction. 
• Cross‑functional alignment: Act as the data ambassador between Product Analytics, core Engineering, Business Intelligence, and Legal—ensuring that RFCs, DB migrations, and new features land with data contracts intact.
• Mentorship: Raise the bar for the team by leading design reviews, establishing style guides, and coaching Product Analysts on advanced SQL patterns, performance tuning, and observability.
• Tooling: Evolve our internal analytics platforms and help to incorporate new tooling to accelerate the analysts at Klaviyo. Able to jump into Airflow, Terraform, RDS, S3, or other infrastructure tools to unblock the team - even if it’s not a core part of the day-to-day.

What excites you:

• Owning the full lifecycle of data pipelines—from event instrumentation guidelines to semantic‑layer metrics and user‑facing dashboards.
• Diving deep into performance bottlenecks (query plans, warehouse sizing, lineage graphs)
• Translating stakeholder needs into elegant, future‑proof data models that “just work.”
• Helping teammates level up through thoughtful reviews and pair‑sessions.

Who you are:

• 5+ years building analytics or data‑engineering solutions in a modern warehouse (Snowflake/BigQuery/Redshift).
• Mastery of SQL (window functions, JSON parsing, dynamic SQL) and dbt—a strong sense for optimizing lineage graphs.
• Strong fluency in at least one object oriented language (Python or R) 
• Proven experience owning multi‑month projects with minimal guidance
• Deep understanding of CI/CD, data‑contract testing, and infrastructure‑as‑code (GitHub Actions, Terraform, Airflow).
• Ability to influence engineers and analysts alike, translating between technical detail and product impact.
• Clear, proactive written and verbal communication—the kind that prevents surprises and builds trust.

Nice to have:

• Experience deploying or refactoring Shiny or other internal data apps (e.g., AWS EC2).
• Prior work with event‑streaming systems, CDC pipelines, or large‑scale schema migration projects.
• Familiarity with experimentation frameworks (e.g., StatSig) and metric‑store/semantic‑layer concepts.

Massach