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Staff Software Engineer – Data Platform
Location
United States
Posted
22 hours ago
Salary
$166.7K - $232K / year
Seniority
Lead
Job Description
Staff Software Engineer – Data Platform
Pantheon Platform
• Take the platform to the next level. Extend our robust, configuration-driven data platform to surface data insights directly within the Product experience, and to power the infrastructure behind Machine Learning and LLM-driven insights. • Enhance platform architecture. Serve as the lead technical member of the Data Platform team, 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). • Build with modern data infrastructure. Work hands-on with Snowflake (including Snowpark for Python), Google Cloud Platform, Airflow , Docker, and Terraform. • Mentor the team. Guide a team of engineers in designing and implementing high impact projects, raising the technical bar across the group. • Own the full lifecycle. Operate in a full DevOps model — development, testing, operations, and support for the systems you build. • Raise the bar. Drive continuous improvement of engineering standards for coding, testing, deployment, and communication. • Partner cross-functionally. Work with Product, Sales, Ops, Finance and other teams to deliver high-impact data solutions and support a self-service, data-driven culture across Pantheon. • Support reliability. Participate in the Data team’s on-call rotation, contributing to the stability, reliability, and performance of Pantheon’s data infrastructure.
Job Requirements
- 8+ years building production data systems, with deep expertise in large-volume data pipelines, cloud databases, and real-time data events.
- Demonstrated experience as a technical lead — mentoring engineers and driving architecture decisions for a team or platform.
- Strong hands-on experience with Python (Python 3).
- Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Firebolt, or Redshift.
- Experience with Google Cloud Platform (preferred) or a comparable cloud environment, plus containers, Kubernetes, and Terraform.
- Familiarity with configuration-driven pipeline design, Airflow, and CI/CD for data workflows.
- Experience building or supporting the data infrastructure behind Machine Learning and LLM applications — feature stores, embedding/vector pipelines, or model-ready data services.
- Hands-on experience using AI tools to accelerate how you work.
Benefits
- Industry competitive compensation and equity plan
- Flexible time off, sick days, and 13 paid holidays
- Comprehensive medical insurance including Health, Dental and Vision
- Paid parental leave (plus fertility, adoption and other family planning benefits)
- In-office workspace (San Francisco & Chicago)
- Monthly allowance for wellness, reading and access to LinkedIn Learning for continued development
- Events and activities both team-based and company wide that inspire, educate and cultivate
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