Staff Software Engineer - Data Platform

Responsibilities

• Extend the configuration-driven data platform to surface product insights and power machine learning and LLM-driven insights.
• Architect and enhance Ingest as a Service, Curation as a Service, and Retention as a Service platform capabilities.
• Build and operate data infrastructure using Snowflake, Snowpark for Python, Google Cloud Platform, Airflow, Docker, and Terraform.
• Serve as the lead technical member of the Data Platform team and guide architecture and implementation of high-impact projects.
• Mentor engineers and raise technical standards for coding, testing, deployment, and communication.
• Own the full development, testing, operations, and support lifecycle for the systems built.
• Partner with Product, Sales, Operations, Finance, and other teams to deliver data solutions.
• Participate in the Data team’s on-call rotation and support infrastructure stability, reliability, and performance.

Requirements

• 8+ years of experience building production data systems, including large-volume pipelines, cloud databases, and real-time data events.
• Deep understanding of distributed data processing, high-throughput and low-latency system design, and scalable data modeling for OLAP and OLTP systems.
• Experience with data governance frameworks, data catalogs, observability tooling, data validation, automated test coverage, and idempotent deployment design.
• Demonstrated technical leadership in setting direction for a platform or team, making architecture decisions, and mentoring engineers.
• Strong hands-on proficiency with Python, including Python 3.
• Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Firebolt, or Redshift.
• Experience with Google Cloud Platform or a comparable cloud environment, containers, Kubernetes, and Terraform.
• Familiarity with configuration-driven pipeline design, Airflow, and CI/CD for data workflows.
• Experience building or supporting infrastructure for machine learning and LLM applications, such as feature stores, embedding/vector pipelines, or model-ready data services.
• Hands-on experience using AI tools to accelerate work and the ability to communicate technical designs and risks to technical and non-technical stakeholders.

Benefits

• Industry-competitive compensation and an equity plan.
• Flexible time off, sick days, and 13 paid holidays.
• Comprehensive medical, dental, and vision insurance.
• Paid parental leave plus fertility, adoption, and other family-planning benefits.
• In-office workspace available in San Francisco and Chicago.
• Monthly allowance for wellness and reading, plus access to LinkedIn Learning.
• Team and company-wide events and activities.
• Visa sponsorship is not available at this time.