Top Data & Analytics Jobs

Lead analytical investigations and build measurement frameworks, dashboards, reporting, and reusable data products for Customer Experience leadership. Partner with data scientists on customer health scoring, forecasting, segmentation, and validation. Use SQL and Python to turn ambiguous business questions into decision-ready insights, document solutions, and operationalize analytics across CX teams.

Lead analytical investigations and build measurement frameworks, dashboards, reporting systems, and reusable Snowflake-backed data products for Customer Experience teams. Partner with data scientists on health scoring, forecasting, segmentation, and validation. Translate ambiguous business questions into decision-ready insights, communicate findings to senior stakeholders, and document solutions for operational handoff.

Leads customer intelligence analytics for the Customer Experience organization by designing measurement frameworks, conducting ambiguous investigations, building dashboards and reusable Snowflake-backed data products, and partnering with data scientists on health scoring, forecasting, segmentation, and validation. Communicates actionable findings to senior stakeholders and operationalizes reporting solutions for scalable handoff.

Lead the technical direction and implementation of Klaviyo’s distributed data platform, including ingestion, streaming, batch processing, storage, governance, and access controls. Establish reliability and freshness SLOs, improve system performance and cost efficiency, standardize data contracts and connectors, and guide incident response. Partner with product, analytics, and ML teams while contributing code, mentoring engineers, and applying AI to data workflows. This is a principal individual-contributor role requiring 10+ years of distributed data systems experience.

Own end-to-end data pipelines and production-grade dbt models (Snowflake) for Sales and Product analytics. Build governed data marts, dimensional models, and reverse ETL workflows. Improve data quality, testing, monitoring, and documentation. Partner with GTM, Product, and BI stakeholders, mentor peers, and contribute to platform tooling (Airflow, Terraform, AWS) to enable reliable, scalable analytics.