PIPELINE - L5 Principal Software Engineer

Klaviyo

Boston (MA)

Sur place

USD 190 000 - 270 000

Plein temps

Il y a 11 jours

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Résumé du poste

Klaviyo is seeking a senior data platform engineer to own the technical direction and delivery for Klaviyo's data platform, including streaming, batch compute, storage/lakehouse, and governance. You will lead through architecture, code, and influence, guiding cross-team collaboration and establishing SLOs for reliability.

You will design scalable data ingestion, streaming, and governance patterns, partner with analytics/ML teams, and drive cost-efficient, high-velocity data workflows with

Qualifications

  • 10+ years building and operating distributed data systems.
  • Experience with multi-tenant reliability and data governance.
  • Experience with ingestion/CDC, stream processing, and lakehouse patterns.

Responsabilités

  • Design and implement core data platform capabilities.
  • Define and uphold SLOs for data freshness, availability, and correctness.
  • Land data contracts, connectors, and templates to accelerate delivery.
  • Profile, tune, and right-size systems for performance and cost.
  • Collaborate with product teams, analytics/ML to enable fast value delivery.
  • Contribute high-quality code, reviews, and mentor engineers.

Connaissances

Distributed data systems
Data ingestion/CDC
Stream processing
Lakehouse patterns
Governance & lineage
SLO definition & reliability
AI tooling in data platforms
Mentoring via docs & pairing

Outils

Kafka
PubSub
Flink
Spark
Beam
Iceberg/Delta/Hudi
Snowflake/BigQuery
Airflow/Dagster

Description du poste

About Klaviyo

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.

Own the technical direction and delivery for Klaviyo's data platform - streaming, batch compute, storage/lakehouse, and governance - now the foundation for autonomous, agent-driven experiences. Klaviyo's data platform processes billions of events daily across billions of consumer profiles for hundreds of thousands of brands, and increasingly that data is consumed not just by people but by a growing number of AI agents acting on customers' behalf. The footprint grows on two axes at once, ever larger data volumes and a steady stream of new data scenarios (new sources, domains, and consumption patterns) and your systems have to scale on both. You'll design and ship systems that are fast, reliable, cost-efficient, and safe for autonomous access, creating paved roads for data producers and consumers, human and agent alike. This is an individual-contributor role (no direct reports); you lead through architecture, code, and influence. Expectations align to Lead/Principal IC behaviors: establishing SLOs, driving technical evolution, and acting as the interface across teams.

What You'll Do
  • Design and implement core data platform capabilities (e.g., event ingestion/CDC, stream processing, batch orchestration, data lake/warehouse patterns, catalog/lineage, governance, access, and compliance).
  • Define and uphold SLOs for data freshness, availability, and correctness; author/run readiness reviews, incident response, and post-incident learning for your domain.
  • Author ADRs/RFCs, land data contracts and schema governance, and standardize connectors and templates that accelerate developer velocity.
  • Profile, tune, and right-size systems for performance and cost; partner with FinOps on unit-economics guardrails.
  • Pair with product teams and analytics/ML to expose the right abstractions and unblock customer value quickly.
  • Contribute high-quality code and reviews; mentor Staff/ Sr. engineers across pillars through example and enablement (not line management).
  • Use AI to streamline data workflows, from authoring and testing pipelines to catalog/search and DQ, so analysts, ML, and product teams move faster with confidence.
Who You Are
  • Experience: 10+ years building and operating distributed data systems (e.g., Kafka/PubSub, Flink/Spark/Beam, Airflow/Dagster, Iceberg/Delta/Hudi; Snowflake/BigQuery; object storage) with multi-tenant reliability.
  • Technical expertise: Data ingestion/CDC, stream processing, batch orchestration, lakehouse patterns, catalog/lineage, governance, and access controls, measured by freshness, availability, and correctness SLOs.
  • AI tools & automation: You apply ML/GenAI to data platforms - semantic catalog search, auto-docs, data-quality anomaly detection, SQL/pipeline generation - with human-in-the-loop review and privacy controls.
  • Influence & enablement: You land data contracts, connectors, and templates that speed delivery for producers and consumers; you mentor via design docs and pairing.
  • AI fluency (Klaviyo default): You experiment, learn fast, and share AI wins responsibly.
Nice to Haves
  • Regional isolation/replication strategies, privacy-by-design, and data governance in regulated contexts.
  • Adopted paved roads: Producers/consumers are on standard ingestion, processing, and storage paths; schema governance and contracts reduce breakage.
  • SLOs & efficiency: ≥99.9% freshness for key domains; measurable cost/TB reductions; production debugging is faster with defined readiness reviews and incident learning.
  • AI-augmented data operations: Semantic discovery and auto-docs cover the majority of high-value datasets; AI-assisted DQ monitors reduce data incidents on top pipelines by 25-40%; pipeline authoring and review times drop 15-25% with AI in the loop.
Success in 6 - 12 Months
  • Adopted 'paved roads' for producers/consumers; ≥99.9% freshness SLO for key domains; measurable cost/TB reductions.
  • One or more step-change improvements (e.g., 2x faster ingest to analytics latency) demonstrated with metrics and post-incident trend-down.
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Equity options
Annual cash bonus
Comprehensive health benefits