Senior Data Engineer, Business Intelligence

Klaviyo is a company that empowers creators to own their destiny by making first-party data accessible and actionable. They are seeking a Senior Data Engineer to join their Business Intelligence team, responsible for creating and maintaining the internal data infrastructure that supports data-driven decision-making across the organization.

Responsibilities:

• Transform workflows by putting AI at the center, building smarter systems and ways of working from the ground up for example, using AI to generate tests, detect anomalies, summarize data issues, or accelerate analysis
• Design, develop, and maintain scalable dbt models and pipelines, including advanced incremental and merge strategies
• Architect solutions for attribution models, event data pipelines, and analytics at scale
• Lead performance optimization efforts across Snowflake and related data systems
• Define and enforce best practices for query performance, warehouse management, and cost control
• Own end-to-end data pipelines, ensuring reliability, scalability, and observability
• Lead complex DAG orchestration with Airflow/MWAA
• Oversee Spark/EMR cluster management, job optimization, and large-scale backfills
• Implement monitoring, alerting, and automated recovery strategies for production systems
• Architect infrastructure-as-code solutions using Terraform for Snowflake and AWS resources
• Oversee integration of AWS services (S3, EMR, Secrets Manager, CloudWatch) into the data platform
• Guide CI/CD pipeline design and improvements using GitHub Actions and CodeBuild
• Promote containerization best practices with Docker for scalable deployments
• Monitor Snowflake and EMR usage to proactively optimize costs
• Analyze query performance and warehouse efficiency
• Troubleshoot and resolve pipeline and infrastructure performance issues
• Mentor and coach junior and mid-level data engineers through code reviews and technical guidance
• Establish and enforce coding standards, testing practices, and CI/CD processes
• Serve as technical lead for cross-functional data initiatives
• Advocate for reliability, performance, and cost optimization across the data engineering function

Requirements:

• 5+ years of data engineering experience, including demonstrated technical leadership
• Expert-level proficiency in dbt, including advanced modeling, testing frameworks, incremental strategies, and performance tuning
• Deep expertise in SQL and Snowflake, including query optimization, warehouse sizing, and cost governance
• Strong Python skills for data processing, API integrations, and internal tooling
• Experience architecting data lakehouse solutions
• Hands-on experience designing and operating Apache Iceberg-based data lake architectures on Amazon EMR
• Proven experience operating production systems with a strong focus on reliability and cost efficiency
• Demonstrated experience leveraging AI to improve personal and team workflows
• Strong problem-solving skills and an operational mindset focused on SLAs and production stability
• Ability to align technical decisions with business priorities
• You've already experimented with AI in work or personal projects, and you're excited to dive in and learn fast. You're hungry to responsibly explore new AI tools and workflows, finding ways to make your work smarter and more efficient
• Expertise in Spark/EMR performance optimization and scaling strategies
• Advanced Terraform usage across multi-environment infrastructure
• Extensive experience with Airflow/MWAA orchestration at scale
• Strong Docker and container orchestration experience
• Experience architecting AI-driven workflows, including multi-agent systems, concurrent execution models, and tool-augmented agents
• Domain experience in: Marketing attribution modeling and analytics data flows, Event data ingestion, transformation, and large-scale aggregation, Data warehouse governance, optimization, and cost modeling, BI infrastructure and operational excellence