Senior Lead Data Platform Engineer - Lakehouse & Cross-Team

Klaviyo Inc.

Boston (MA)

Hybrid

USD 216,000 - 324,000

Full time

14 days+
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Job summary

Klaviyo Inc. in the United States seeks a Senior Lead Software Engineer for the Data Platform, anchored in the Data Lake domain, to shape technical direction and align roadmaps across teams.

You will own high-impact initiatives spanning lakehouse storage and compute, data onboarding and orchestration, and modeled data layers, while mentoring engineers and communicating with partners.

You’ll drive reliability, observability and cost-aware operations at scale.

Qualifications

  • You have 12+ years of software engineering experience with distributed systems and data platforms.
  • You have led large, ambiguous programs and made clear architectural calls across teams.
  • You understand lakehouse, data ingestion, transformation, and governance within cloud data platforms.

Responsibilities

  • Own high-impact objectives spanning multiple Data Platform teams, especially Data Lake.
  • Align roadmaps and dependencies across teams to ensure coherent platform direction.
  • Lead cross-team initiatives from discovery to rollout and long-term ownership.
  • Make architectural decisions across lakehouse storage, compute, and orchestration.
  • Establish standards and patterns to improve onboarding, operation, and reliability.

Skills

Distributed systems
Data platform architecture
Lead large programs
Cloud platforms (AWS)
Iceberg storage
Spark/EMR compute
Airflow orchestration
Python tooling

Tools

Iceberg
Spark
EMR
Airflow
Python
AWS

Job description

Klaviyo Inc. in the United States seeks a Senior Lead Software Engineer for the Data Platform, anchored in the Data Lake domain, to shape technical direction and align roadmaps across teams.

You will own high-impact initiatives spanning lakehouse storage and compute, data onboarding and orchestration, and modeled data layers, while mentoring engineers and communicating with partners.

You’ll drive reliability, observability and cost-aware operations at scale.

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