Senior Software Engineer - Analytics Data Engineering

Klaviyo Klaviyo · Enterprise · Boston, MA · Engineering

This role focuses on building and owning the data foundations that power Klaviyo's Analytics & AI engine. The Senior Software Engineer will design and implement scalable data pipelines and analytics models to transform large volumes of event data into actionable insights, enabling AI/ML products and customer-facing analytics features. The role involves collaborating with AI/ML teams, mentoring other engineers, and evolving technical standards for data engineering.

What you'd actually do

  1. Lead the design and implementation of robust, scalable data pipelines and core tables for Klaviyo. These pipelines are crucial for powering customer facing analytics features and powering AI models to unlock the next stage of Klaviyo's products
  2. Partner with Product, Engineering, and AI/ML teams to define clear, consistent metrics and data contracts that align to business goals and product outcomes.
  3. 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.
  4. Mentor other engineers in data engineering best practices, code quality, observability, and system design; contribute to shared libraries, patterns, and tooling that improve developer velocity across R&D.

Skills

Required

  • 6+ years of software engineering with at least 4 or those being data engineering experience
  • strong track record building and operating data pipelines and analytics models in production
  • Deep proficiency in large-scale SQL and data modeling for analytics
  • Strong programming skills in a modern language commonly used for data engineering (e.g. Python)
  • familiarity with orchestration and transformation tooling (e.g., Airflow, EMR, Spark/pyspark, or equivalents)
  • Experience working with modern data platforms (e.g., columnar data warehouses, object storage) and processing frameworks (batch and/or streaming)
  • Demonstrated ability to lead complex projects spanning multiple components and engineers
  • Comfortable owning systems in production: you think about observability, incident response, incremental rollouts, and long-term maintainability as part of the design.
  • Excellent communication skills

Nice to have

  • Experience in a product-led SaaS environment with large-scale event data
  • Experience in a customer facing data engineering role supports AI/ML features and Analytics Dashboards.
  • Hands-on work with analytics engineering tools and practices (e.g., dbt, metrics layers, semantic models).
  • Experience building near real-time or streaming pipelines for user-facing analytics or monitoring.
  • Domain experience in martech, marketing automation, or customer engagement platforms.

What the JD emphasized

  • AI & Analytics Data Enablement
  • AI and Analytics data
  • AI and Analytics data
  • AI/ML products at scale
  • AI in work or personal projects
  • AI tools and workflows

Other signals

  • powering AI & Analytics experiences for our customers
  • powering AI models to unlock the next stage of Klaviyo's products
  • Partner with Product, Engineering, and AI/ML teams to define clear, consistent metrics and data contracts
  • 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.