PIPELINE - L5 Principal Software Engineer
Klaviyo · Boston, MA
About this role
**PIPELINE - L5 Principal Software Engineer** *At Klaviyo, we value the unique backgrounds, experiences, and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace. If you’re a close but not exact match, we still encourage you to apply.* --- ## Own the technical direction and delivery Own the technical direction and delivery for Klaviyo’s data platform—**streaming, batch compute, storage/lakehouse, and governance**—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**. As data consumption grows beyond people to AI agents acting on customers’ behalf, your systems must scale across both **data volume** and **new data scenarios**. This is an **individual-contributor role (no direct reports)**. You’ll lead through **architecture, code, and influence**, aligned with 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. - Author **ADRs/RFCs**, land data contracts and schema governance, and standardize connectors/templates to 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/testing pipelines to catalog/search and data quality—so analysts, ML, and product teams move faster with confidence. --- ## Who you are - **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. - Strong technical expertise in **data ingestion/CDC, stream processing, batch orchestration, lakehouse patterns, catalog/lineage, governance, and access controls**, measured by **freshness, availability, and correctness SLOs**. - Experience applying **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. - Ability to land **data contracts, connectors, and templates** that speed delivery; mentor via design docs and pairing. - **AI fluency**: 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**” for producers/consumers (standard ingestion/processing/storage paths; schema governance/contracts reduce breakage). - **SLOs & efficiency** (e.g., ≥99.9% freshness for key domains; measurable cost/TB reductions; faster production debugging via readiness reviews and incident learning). - AI-augmented data operations (semanti
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