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Pantheon

Staff Software Engineer - Data Platform

RemoteUnited States only
Published
Role
Data Engineering
Experience
Staff
Employment
Full-time
$166.7k–$232k/yr
Check eligibility

Open to US only. Set where you work from to check your eligibility.

No BS summary

Staff-level software engineer for a US-remote data platform role. Needs 8+ years building production data systems, strong Python 3, cloud data warehouses, GCP or comparable cloud, containers, Kubernetes, Terraform, Airflow, and ML/LLM data infrastructure. Visa sponsorship is not available.

Core skills

PythonSnowflake/BigQuery/Firebolt/RedshiftAirflow

Required skills

GCPContainersKubernetesTerraformCI/CD

Optional skills

GCP

What you'll do

  • 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, Curation as a Service and Retention as a Service.
  • 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.

What they require

  • Distributed data systems: 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.
  • Data modeling and architecture: ability to design, implement, and optimize scalable data models (dimensional, normalized) for both OLAP and OLTP systems, ensuring data integrity and query performance.
  • Data governance & observability: experience with data governance frameworks, data catalogs, and observability tooling that keep large-scale data assets discoverable, trusted, and compliant.
  • Technical leadership: experience setting technical direction for a platform or team, translating ambiguous requirements into clear architecture, and mentoring other engineers.
  • Customer/product focus: 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.
  • Communication: 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.
  • Quality mindset: experience embedding automated test coverage, data validation, and idempotent design into deployment pipelines.
  • Design principles: security, trust, and dependability are foundational to how you build — declarative design, modularity, containers, and idempotency should genuinely excite you.
  • Experience: 8+ years building production data systems, with deep expertise in large-volume data pipelines, cloud databases, and real-time data events.
  • Track record: demonstrated experience as a technical lead — mentoring engineers and driving architecture decisions for a team or platform.
  • Coding proficiency: strong hands-on experience with Python (Python 3).
  • Database knowledge: hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Firebolt, or Redshift.
  • Cloud & infrastructure: experience with Google Cloud Platform (preferred) or a comparable cloud environment, plus containers, Kubernetes, and Terraform.
  • Modern data stack: familiarity with configuration-driven pipeline design, Airflow, and CI/CD for data workflows.
  • ML/LLM infrastructure: experience building or supporting the data infrastructure behind Machine Learning and LLM applications — feature stores, embedding/vector pipelines, or model-ready data services.
  • AI-forward: hands-on experience using AI tools to accelerate how you work.
  • Team mindset: you take pride in what your team accomplishes, not just your individual output, and communicate with clarity and openness.
  • Visa Sponsorship is not available at this time.
  • After an offer is made and accepted, E-verify will be utilized to establish your identity and employment eligibility as required by the U.S. Department of Homeland Security.

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
Information Technology

Details

Visa sponsorshipNo
$166.7k–$232k/yr