Director of Engineering, Platform Infrastructure

Klaviyo•Boston, MA

41d

About The Position

Founded in 2012, Klaviyo was built around data processing and analytics from the start. Over the years our data foundation has evolved to a multi-tier architecture, supporting transactional access, real-time analytics, and off-line data processing jobs at multi-petabyte scale. As Klaviyo diversifies and moves up-market, and as the pace of machine learning advancement increases, the requirements on and importance of the data platform continue to rapidly grow. Our team has a wide mix of talents and experience, and we are uniquely positioned to advance the state of the practice by applying what we have learned in the past to the challenges of the future. As Head of Data Platform, you will report directly to the VP of Data Infrastructure Engineering. You will own the data lake, on-line analytics systems, data ingestion and movement, query processing, automation, compliance, and other related areas, and will coordinate the efforts of those teams to build our next generation of data platform that meets our scale, performance, reliability, and flexibility requirements. How you'll make a difference: Your work will be foundational, enabling machine learning (ML), artificial intelligence (AI), business intelligence (BI), and advanced analytics (AA) product features across the organization, while directly contributing to Klaviyo's strategic growth in the mid-market (MM+) segment and expansion into new verticals. You will do this by leading teams to build a data platform that is accessed through a clear and cohesive set of APIs which could enable it to become a product itself.

Requirements

Deep Technical Expertise: Extensive experience in designing, building, and operating large-scale data platforms, distributed systems, and data warehousing solutions. Experience working with technologies such as Kafka, Iceberg, Snowflake, Airflow, Clickhouse, MySQL/Postgres, etc.
Strategic Leadership: Proven ability to define and execute complex technical strategies, manage trade-offs, and secure cross-organizational commitment for foundational initiatives.
Team & Organizational Development: Experience in leading and growing high-performing engineering teams, fostering a culture of ownership, innovation, and operational excellence.
Problem-Solving Acumen: A track record of identifying critical pain points in data management (e.g., data silos, performance bottlenecks, cost inefficiencies) and delivering impactful solutions.
Customer-Centric Mindset: An understanding of how data infrastructure directly impacts customer experience, product adoption, and business revenue.

Responsibilities

Drive Vision & Strategy: Lead the strategic planning, architectural design, and execution for the Data Platform, ensuring alignment with overall company objectives to dominate retail marketing and productize AI agents.
Build Foundational Data Capabilities: Oversee the development of core data structures, including a Common Data Model (CDM), unified data collection via Change Data Capture (CDC), and a scalable Key Value Store (KVS), serving as the bedrock for flexible data models and future innovations.
Enhance Data Access & Performance: Lead efforts to significantly improve data discovery, exploration, querying capabilities, and reducing processing times for ML, BI, and analytical use cases.
Scale for Growth: Ensure the platform's scalability and reliability to support multiple customers with over 100M profiles by 2026, improving event processing, and reducing profile ingest times, all while controlling costs.
Improve Data Quality & Governance: Champion initiatives for data quality, transactional consistency, GDPR compliance, and rigorous data governance, including data access control and operating in multiple geographies.
Foster Internal & External Partnerships: Collaborate closely with internal teams (Data Science, BI, Product Analytics, Application Developers) and prepare for externalizing data platform services for third-party developers.

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