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Engineering Manager, Profile Traits

External
Klaviyo logoKlaviyo · Boston, MA
Full-timeOn-site1mo ago
AWSData ModelingObservabilityPython
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About the role

The Profile Traits team owns how customer profile data is represented, stored, mutated, and served across Klaviyo. Profile traits are one of the most critical primitives in the platform: they power segmentation, personalization, flows, analytics, and emerging AI-driven features. As Engineering Manager, Profile Traits , you will lead a team of engineers responsible for building and scaling these foundational systems. This role sits at the intersection of distributed systems, data modeling, and product semantics, with a strong emphasis on correctness, performance, and long-term platform evolution. You will partner closely with product managers and adjacent platform teams (Events, Identity & Consent, Segmentation, Flows) to ensure profile data remains reliable, fast, and easy to reason about as Klaviyo continues to grow.

Responsibilities

  • Lead, mentor, and grow a team of engineers building Klaviyo's profile traits platform
  • Own systems responsible for profile attribute storage, mutation, and serving
  • Drive technical and execution excellence across correctness, latency, and cost
  • Partner with product and platform teams to define roadmaps and priorities
  • Guide architectural decisions around schema evolution, consistency, and scale
  • Participate in design and code reviews to maintain a high technical bar
  • Foster a culture of ownership, collaboration, and continuous improvement
  • High-QPS, stateful systems supporting real-time and nearline profile updates
  • Schema evolution and backward compatibility for long-lived customer data
  • Mechanisms for trait computation, backfills, and data migrations
  • Improving debuggability, observability, and operational maturity
  • Scaling profile read and write paths to support new product capabilities
  • Who You AreRequired Qualifications
  • 8-10+ years of software engineering experience
  • 3+ years of engineering management experience
  • Experience owning and evolving stateful or data-intensive systems at scale
  • Strong understanding of distributed systems tradeoffs
  • Proven ability to coach and develop senior engineers
  • Experience partnering with Product on ambiguous, platform-oriented problems

Requirements

  • Experience with high-QPS OLTP systems
  • Background in data consistency, data modeling, or schema evolution
  • Experience supporting both online and analytical workloads
  • Familiarity with cloud-native systems (AWS preferred)
  • Why This Role Matters
  • Technologies We Use
  • Our stack evolves with our needs, but today includes:
  • Distributed services built primarily in Python and Go
  • Cloud infrastructure on AWS
  • Stream processing and data pipelines at scale
  • A mix of real-time, nearline, and analytical data systems
  • Please see the independent bias audit report covering our use of Covey here
  • 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.
  • In a

Additional Information

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. Hybrid 3x/week out of Boston. At Klaviyo, we empower creators and businesses to own their customer relationships. Our platform processes billions of events and powers real-time personalization, automation, and analytics for thousands of customers. At the core of this platform is our data infrastructure - the systems that ingest, store, transform, and serve customer data at scale.


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