Senior Data Engineer

Design, build, and optimize robust, scalable, and reliable data pipelines to ingest and process data from a wide variety of sources.

Develop and maintain our data warehousing solutions (e.g. Snowflake), including maintenance of an advanced RBAC model to ensure data governance throughout all data tooling.

Ensure data quality and integrity by implementing data validation frameworks, monitoring systems, and anomaly detection protocols.

Architect and manage cloud-based data infrastructure.

Orchestrate batch machine learning pipelines. Work closely with data scientists to orchestrate code based on data science and product requirements, getting alignment on optimizations when necessary.

Collaborate with stakeholders, including data scientists, analysts, and product managers to understand data requirements and deliver actionable solutions.

Improve performance, efficiency and optimize cost of existing data systems and processes.

Work alongside Data and Engineering leadership to weigh tradeoffs in build vs buy decisions and tradeoffs in product roadmap vs technical initiatives.

Work with internal software engineering teams to define architectures and best practices for ingesting data into the data warehouse and making aggregated data and metrics from the data warehouse available to our production applications.

Interact with vendors to craft the adoption of new technology and infrastructure for the team.

Designs, develops, and evaluates AI agents and reusable skill libraries to drive developer productivity and automate team workflows — including prompt engineering, tool integration, and performance evaluation using platforms such as Snowflake Cortex AI and LangGraph.

Architects and governs secure integrations between enterprise AI tools (Claude, Cursor, Gemini, Slack, etc.) and the data warehouse, ensuring data access controls, auditability, and compliance standards are maintained across the AI toolchain.

Take part in an on-call rotation. Work with Engineering leadership to define SLAs and alerting policies for our systems.

Lead and participate in incident management, ensuring clear and timely communication with stakeholders.

Write new and enhance existing technical and functional documentation on Data Engineering-owned systems and standards. Proactively address gaps in existing team standards, SLAs, operating principles, and documentation and work with leadership to scope and implement improvements in these areas.

Be a leader, mentor, and subject matter expert for the team, stakeholders, and peers. Foster a collaborative environment that drives solutions forward at a larger scope.