Staff Software Engineer - Data Platform

Role Description

The Data Platform team powers Pantheon’s data infrastructure and delivers analytics across the company. We’ve built a robust, configuration-driven data platform that handles extraction, ingestion, curation, compliance, security, and enterprise-wide access to data — and we’re looking for a Staff Software Engineer to take it to the next level.

• Extend the platform beyond its current foundation to surface data insights directly within our Product experience, and to power the infrastructure behind Machine Learning and LLM-driven insights.
• 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)
• Retention as a Service (historical data hosting that balances access, compliance, and cost)
• Work hands-on with Snowflake (including Snowpark for Python), Google Cloud Platform, Airflow, Docker, and Terraform.
• Guide a team of engineers in designing and implementing high impact projects, raising the technical bar across the group.
• Operate in a full DevOps model — development, testing, operations, and support for the systems you build.
• Drive continuous improvement of engineering standards for coding, testing, deployment, and communication.
• 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.
• Participate in the Data team’s on-call rotation, contributing to the stability, reliability, and performance of Pantheon’s data infrastructure.

Qualifications

• Deep understanding of processing large-scale datasets across distributed systems, with a clear grasp of the trade-offs in designing for high throughput and low latency.
• Ability to design, implement, and optimize scalable data models (dimensional, normalized) for both OLAP and OLTP systems, ensuring data integrity and query performance.
• Experience with data governance frameworks, data catalogs, and observability tooling that keep large-scale data assets discoverable, trusted, and compliant.
• Experience setting technical direction for a platform or team, translating ambiguous requirements into clear architecture, and mentoring other engineers.
• An understanding of the direct and indirect business value of your work, ensuring data solutions align with company-wide goals and deliver impact for internal and external customers.
• The ability to clearly articulate technical designs, project status, and risk to both technical peers and non-technical stakeholders, while remaining open to others’ ideas.
• Experience embedding automated test coverage, data validation, and idempotent design into deployment pipelines.
• Security, trust, and dependability are foundational to how you build — declarative design, modularity, containers, and idempotency should genuinely excite you.

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.
• You take pride in what your team accomplishes, not just your individual output, and communicate with clarity and openness.

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