Staff Software Engineer – Data Platform

This is a fully remote position, open to applicants in United States.

📋 Description

• Elevate the platform to new heights by enhancing our robust, configuration-driven data platform to present data insights directly within the Product experience and to support the infrastructure for Machine Learning and LLM-driven insights.

• Improve platform architecture by acting as the lead technical contributor on the Data Platform team, while maintaining and enhancing our core platform services: Ingest as a Service (consistent extraction and loading into the data lake), Curation as a Service (configuration-driven, audited transformations), and Retention as a Service (historical data hosting that balances access, compliance, and cost).

• Develop using modern data infrastructure, engaging hands-on with Snowflake (including Snowpark for Python), Google Cloud Platform, Airflow, Docker, and Terraform.

• Provide mentorship to the team by guiding engineers in designing and implementing impactful projects, thereby raising the technical standards across the group.

• Take ownership of the entire lifecycle by operating within a full DevOps model — encompassing development, testing, operations, and support for the systems you create.

• Strive for excellence by driving continuous enhancements in engineering standards for coding, testing, deployment, and communication.

• Collaborate cross-functionally with Product, Sales, Ops, Finance, and other teams to deliver high-impact data solutions and foster a self-service, data-driven culture throughout Pantheon.

• Ensure reliability by participating in the Data team’s on-call rotation, contributing to the stability, reliability, and performance of Pantheon’s data infrastructure.

⛳️ Requirements

• 8+ years of experience in building production data systems, with extensive expertise in large-volume data pipelines, cloud databases, and real-time data events.

• Proven track record as a technical lead — mentoring engineers and making architectural decisions for a team or platform.

• Strong practical experience with Python (Python 3).

• Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Firebolt, or Redshift.

• Familiarity with Google Cloud Platform (preferred) or a similar cloud environment, as well as containers, Kubernetes, and Terraform.

• Knowledge of configuration-driven pipeline design, Airflow, and CI/CD for data workflows.

• Experience in building or supporting the data infrastructure for Machine Learning and LLM applications — such as feature stores, embedding/vector pipelines, or model-ready data services.

• Practical experience utilizing AI tools to enhance productivity.

🏝️ Benefits

• Industry competitive compensation and equity plan.

• Flexible time off, sick days, and 13 paid holidays.

• Comprehensive medical insurance, including Health, Dental, and Vision coverage.

• Paid parental leave (including benefits for fertility, adoption, and other family planning).

• In-office workspace options available in San Francisco & Chicago.

• Monthly allowance for wellness, reading, and access to LinkedIn Learning for ongoing professional development.

• Team-based and company-wide events and activities that inspire, educate, and cultivate.