Key skills
PythonAIMachine LearningLLMData LakeSnowflakeBigQueryRedshiftAirflowGoogle CloudTerraformKubernetesDockerCI/CDCommunicationSales
About this role
Pantheon is a WebOps Platform that powers the open web, serving over 300,000 sites for various customers. They are seeking a Staff Software Engineer to enhance their data platform, enabling data insights and supporting Machine Learning applications while collaborating with multiple teams to deliver high-impact data solutions.
Responsibilities:
- 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
- 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)
- 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
Requirements:
- Deep understanding of processing large-scale datasets across distributed systems
- Ability to design, implement, and optimize scalable data models (dimensional, normalized) for both OLAP and OLTP systems
- Experience with data governance frameworks, data catalogs, and observability tooling
- Experience setting technical direction for a platform or team
- Understanding of the direct and indirect business value of your work
- Ability to clearly articulate technical designs, project status, and risk to both technical peers and non-technical stakeholders
- Experience embedding automated test coverage, data validation, and idempotent design into deployment pipelines
- Security, trust, and dependability are foundational to how you build
- 8+ years building production data systems
- Demonstrated experience as a technical lead
- Strong hands-on experience with Python (Python 3)
- Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Firebolt, or Redshift
- Experience with 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
- Team mindset
- Experience with Google Cloud Platform (preferred) or a comparable cloud environment
- Hands-on experience using AI tools to accelerate how you work