Principal Data Engineer

7+ years of experience building reliable, performant data systems, including data modeling, ETL/ELT pipelines, and warehouse optimization.
Comfortable with SQL and Python (or similar languages), and hands-on experience with tools like dbt, Airflow, Redshift, Snowflake, or other cloud-native data platforms.
Experience designing systems with built-in privacy, access controls, and governance. Familiarity with secure data handling, regulatory compliance, and data classification in multi-tenant or regulated environments.
Ability to work across product, engineering, and analytics teams to shape systems that deliver long-term value.

Help define and deliver a data platform roadmap that supports near-term needs and long-term scale—enabling insights, innovation, and customer value across our products and analytics ecosystem.
Build robust systems to ingest, transform, store, and serve data across multi-tenant and single-tenant use cases—balancing flexibility, security, and performance.
Develop reliable and observable pipelines using modern batch and near real-time approaches, connecting internal and external data sources.
Advance practices in data quality, observability, and governance—ensuring our systems are secure, compliant, auditable, and built to meet customer and regulatory expectations.
Work closely with the analytics and product teams to deliver structured, reliable data pipelines that support a growing ecosystem of dashboards, customer-facing analytics, and research—providing the trusted foundation for downstream insights.
Provide guidance, share knowledge, and lead by example to establish best practices and grow the data engineering function.
Partner with cross-functional leaders to define and evolve a data platform roadmap that grows with our customers, products, and teams.

Experience designing backend systems that power customer-facing analytics or data-driven product features.