Staff Software Engineer – Data Platform

Pantheon Platform

Staff Software Engineer enhancing Pantheon’s data infrastructure and delivering analytics across the company while mentoring data engineers. Guiding platform architecture and building modern data solutions.

Posted 7/9/2026full-timeRemote • 🇺🇸 United StatesLead💰 $166,700 - $232,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftBigQueryCloudDockerGoogle Cloud PlatformKubernetesPythonTerraform

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Large-Volume Data PipelinesCloud DatabasesReal-Time Data EventsConfiguration-Driven Pipeline DesignCI/CD for Data Workflows

Soft Skills

MentoringCross-Functional Collaboration