Software Engineer II - Analytics Data Engineering
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.
Software Engineer II - Analytics Data Engineering | AI & Analytics Data Enablement
Location: Boston, MA
About the Role
Data is the lifeblood of Klaviyo. As a Data Engineer on this team, you will sit at the intersection of infrastructure and intelligence. You won’t just be moving data; you’ll be building the foundations that power our next generation of AI-driven features and enterprise-scale analytics.
You will bridge the gap between data engineering and product impact. Your work will involve developing scalable Spark pipelines, tuning our storage and query patterns to ensure low-latency performance for our enterprise customers, and modeling the high-impact datasets that drive Klaviyo's analytics and machine learning engines.
What You’ll Do
- Build Production-Grade Foundations: Develop and maintain scalable data pipelines and core tables using PySpark, Airflow, and dbt. You will implement the foundational datasets that power our AI, ML, and Analytics products.
- Optimize for Enterprise Performance: Tune Spark jobs and storage patterns to ensure low-latency data retrieval. You will help implement materialized views and efficient partitioning strategies to support high-performance reporting at scale.
- Treat Data as a Product: Contribute to the full lifecycle of datasets. This includes defining clear data contracts with upstream teams, writing maintainable code via peer reviews, and ensuring every asset is well-documented and trusted by downstream users.
- Drive Operational Excellence: Ensure the reliability of our data engine by monitoring for freshness, volume anomalies, and schema changes. You will be responsible for ensuring that when a customer loads a dashboard, the data is accurate and on time.
- Partner Cross-Functionally: Collaborate with Product, Engineering, and AI/ML teams to define consistent metrics that align with business goals. You will act as a bridge to ensure new features land with robust data support.
- Innovate with AI: Look for opportunities to put AI at the center of your workflow, whether it is using AI to generate tests, detect data anomalies, or accelerate complex analysis.
Who You Are
- The Experience: 2+ years of experience in data engineering or a data-intensive software engineering role. You’ve moved past the "beginner" phase and are comfortable taking a project from a design doc to a production deployment.
- Fluent in SQL and Python: You have a solid grasp of SQL for high-performance querying and are comfortable using Python for data manipulation and automation. You focus on writing code that balances speed with reliability.
- Distributed Systems Knowledge: You have hands-on experience with Spark (PySpark/SparkSQL) and understand how to tune jobs for performance in a cloud environment (AWS/EMR).
- Modeling Intuition: You understand the difference between a "raw table" and a "semantic layer." You’ve worked with modern modeling tools (like dbt) and understand partitioning, schema evolution, and lakehouse concepts (Iceberg/Delta).
- Performance Minded: You care about latency. You enjoy the challenge of making a query run faster and understand how to use materialized views and caching effectively.
- Collaborative & Curious: You’re an inclusive collaborator who enjoys working with Product and Data Science. You’re excited to experiment with AI tools to make your own engineering workflow more efficient.
Nice to Haves
- Experience with Iceberg table maintenance and compaction.
- Exposure to Terraform or other Infrastructure-as-Code tools.
- A background in Martech or SaaS platforms dealing with high-frequency event data.
- Experience building data products that directly power customer-facing UI components and/or support AI/ML features.
- Experience building near real-time or streaming pipelines for user-facing analytics or monitoring.
- Hands-on work with analytics engineering tools and practices (e.g., dbt, metrics layers, semantic models).
- Familiarity with statistical modeling and machine learning.
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.
