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 klaviyo.com/careers to see how we empower creators to own their own destiny.
Data is at the heart of every decision made at Klaviyo, and we’re looking for a Business Intelligence Data Engineer to join our Go To Market (GTM) team supporting Sales Analytics. This domain of data aims to improve the experience of Sales Operations and Analytics. Secondary to this, the role will support ancillary functions of the Partnerships Organization and collaborate with the CS&S organization. This role sits in Data Engineering as part of the GTM team, which is part of a hub and spoke model of analytics engineering at Klaviyo.
You’ll build and steward the source of truth for Sales Operational data so People leaders and analysts can answer questions quickly and confidently and turn those insights into a more incentivized, higher-performing organization. You will directly support the sales analytics teams at Klaviyo, working cross functionally with Systems, Deal Ops,, Audits, Planning, and Business Intelligence.
You will be an independent self-serving, embedded partner to all of GTM leadership where Sales subject matter expertise is required, capable of translating ambiguous requirements into stable data products. You’ll be supported by the broader Data Engineering organization’s standards, tooling, and review practices.
How you’ll make a difference- Deliver Sales specific data modeling that drives better operational experience, is SOX compliant, and provides detailed insight into the day to day of operation as well as forecasting. Maintain and stand up curated, documented marts that make it easy for analytics to operate within a structured governance mandate that enables the Sales operations team to work fast and focus on their organizations with the safety of production ready data.
- Own the pipelines & models end‑to‑end. Build and maintain reliable integrations from core sales systems (e.g., CRMs/ROP/ERPs), model them in dbt, and publish governed marts and reverse‑ETLs to operational destinations where they create value.
- Create attainment views with Compensation and People Analytics. Partner with analysts to build holistic views of the Sales lifecycle. Examples of focus are quicker cadences to booking and dynamic reconciliation processes
- Raise the bar on data reliability and governance. Instrument monitoring and alerting, tests (freshness/volume/constraints), and documentation so the sales data ecosystem is discoverable, auditable, and self-serveable.
- Operate as a trusted partner to leadership. Work directly with Operations and Sales leadership to scope problems, clarify trade‑offs, and communicate technical concepts in exec‑ready language.
- Integrations & ingestion: Own secure ingestion from ROP/ERP/performance systems into Snowflake; define SLAs/SLOs; implement monitoring & alerting for each feed.
- Modeling & marts: Design dimensional/entity models (dbt) for employees, positions, org structure, performance history, forecasting, and pipeline movement; publish curated marts with strong contracts and lineage.
- Reverse ETL: Operationalize high‑value models to downstream tools and workflows using reverse‑ETL patterns to close the loop between insight and action.
- Quality & governance: Implement tests (unit/integration, schema/freshness), multi-layered validation frameworks that routinely validate data integrity, data policies (masking, purpose‑based access), and documentation that enable safe self‑service across the analytics community.
- Repository stewardship: Maintain the analytics codebase (dbt repo), perform code reviews, and ensure modular, reusable patterns the broader team can adopt.
- Stakeholder partnership: Run an intake & engagement model with Revenue and Sales Operations/ Analytics (primary), HRIS/People Tech (security/integration), Finance (plan/comp interfaces), and BI/Platform teams (shared standards).
- 3–5+ years in analytics/data engineering with production ELT in Snowflake + dbt + SQL; Python for orchestration/utilities.
- Strong demonstration of Sales Operations
- Demonstrated independence partnering with senior, non‑technical leaders; able to translate open‑ended needs into scalable data products.
- Proven experience implementing tests, monitoring, and documentation that keep pipelines healthy and reporting trustworthy.
- Experience building data integrations and reverse‑ETL pipelines that support business operations.
- Airflow (orchestration) and Fivetran/Workato (ELT/integration).
- Familiarity with data privacy controls (masking/RLS) in people data.
- AWS experience (S3/EC2/Lambda) and IaC/Terraform.
Snowflake, dbt, Airflow, Fivetran, Workato, Python, AWS, Tableau/Looker/ThoughtSpot; publishing via reverse‑ETL where appropriate.
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.
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.
By participating in Klaviyo’s interview process, you acknowledge that you have read, understood, and will adhere to our Guidelines for using AI in the Klaviyo interview Process. For more information about how we process your personal data, see our Job Applicant Privacy Notice.
Klaviyo is committed to a policy of equal opportunity and non-discrimination. We do not discriminate on the basis of race, ethnicity, citizenship, national origin, color, religion or religious creed, age, sex (including pregnancy), gender identity, sexual orientation, physical or mental disability, veteran or active military status, marital status, criminal record, genetics, retaliation, sexual harassment or any other characteristic protected by applicable law.
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Klaviyo Boston, Massachusetts, USA Office
We're in the heart of the Financial district with easy access to public transportation and a short walk from South Station. We also have hubs in Denver, London and Sydney.
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