
Senior Data Engineer, Business Intelligence
- Company name
- Klaviyo (website)
- Annual base salary
- $124,000 — $186,000
- Location
On-site from
- Posted on SalaryPine
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.
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.
Data is at the heart of every decision made at Klaviyo, and we’re looking for a Senior Data Engineer to join our Business Intelligence (BI) team. BI at Klaviyo collaborates across all departments to provide a platform that powers all internal data, analytic, and reporting needs. Our mission is to champion data-driven value creation, and you will own creating and maintaining the internal data infrastructure that powers Klaviyo’s business. This role in particular will significantly contribute to the infrastructure, pipelines, and security/compliance aspects of our internal analytics platform while driving architectural innovation and mentoring the team.
How You’ll Make a Difference
As a Senior Data Engineer, you will shape the scalability, reliability, and cost-efficiency of our data platform. You’ll lead architectural decisions, establish engineering best practices, and mentor other engineers while partnering closely with analytics, engineering, and business stakeholders.
Your work will directly influence data-driven decision-making across the organization by ensuring our data systems are performant, observable, and built to scale.
What You’ll Do (Responsibilities)
Accelerating Engineering with AI
- Transform workflows by putting AI at the center, building smarter systems and ways of working from the ground up for example, using AI to generate tests, detect anomalies, summarize data issues, or accelerate analysis.
Data Architecture & Optimization
- Design, develop, and maintain scalable dbt models and pipelines, including advanced incremental and merge strategies.
- Architect solutions for attribution models, event data pipelines, and analytics at scale.
- Lead performance optimization efforts across Snowflake and related data systems.
- Define and enforce best practices for query performance, warehouse management, and cost control.
Pipeline & Platform Ownership
- Own end-to-end data pipelines, ensuring reliability, scalability, and observability.
- Lead complex DAG orchestration with Airflow/MWAA.
- Oversee Spark/EMR cluster management, job optimization, and large-scale backfills.
- Implement monitoring, alerting, and automated recovery strategies for production systems.
Infrastructure & DevOps Leadership
- Architect infrastructure-as-code solutions using Terraform for Snowflake and AWS resources.
- Oversee integration of AWS services (S3, EMR, Secrets Manager, CloudWatch) into the data platform.
- Guide CI/CD pipeline design and improvements using GitHub Actions and CodeBuild.
- Promote containerization best practices with Docker for scalable deployments.
Cost & Performance Management
- Monitor Snowflake and EMR usage to proactively optimize costs.
- Analyze query performance and warehouse efficiency.
- Troubleshoot and resolve pipeline and infrastructure performance issues.
Leadership & Mentorship
- Mentor and coach junior and mid-level data engineers through code reviews and technical guidance.
- Establish and enforce coding standards, testing practices, and CI/CD processes.
- Serve as technical lead for cross-functional data initiatives.
- Advocate for reliability, performance, and cost optimization across the data engineering function.
Who You Are (Qualifications)
- 5+ years of data engineering experience, including demonstrated technical leadership.
- Expert-level proficiency in dbt, including advanced modeling, testing frameworks, incremental strategies, and performance tuning.
- Deep expertise in SQL and Snowflake, including query optimization, warehouse sizing, and cost governance.
- Strong Python skills for data processing, API integrations, and internal tooling.
- Experience architecting data lakehouse solutions.
- Hands-on experience designing and operating Apache Iceberg-based data lake architectures on Amazon EMR.
- Proven experience operating production systems with a strong focus on reliability and cost efficiency.
- Demonstrated experience leveraging AI to improve personal and team workflows.
- Strong problem-solving skills and an operational mindset focused on SLAs and production stability.
- Ability to align technical decisions with business priorities.
- You’ve already experimented with AI in work or personal projects, and you’re excited to dive in and learn fast. You’re hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient.
Nice to Haves
- Expertise in Spark/EMR performance optimization and scaling strategies.
- Advanced Terraform usage across multi-environment infrastructure.
- Extensive experience with Airflow/MWAA orchestration at scale.
- Strong Docker and container orchestration experience.
- Experience architecting AI-driven workflows, including multi-agent systems, concurrent execution models, and tool-augmented agents.
- Domain experience in:
- Marketing attribution modeling and analytics data flows
- Event data ingestion, transformation, and large-scale aggregation
- Data warehouse governance, optimization, and cost modeling
- BI infrastructure and operational excellence
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.
Base Pay Range For US Locations:$124,000—$186,000 USDGet 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.