Staff Software Engineer – Data Platform

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Logo of Pantheon Platform

Pantheon Platform

501 - 1000 employees

💼 Consulting

📣 Marketing

☁️ SaaS

Consulting • Marketing • SaaS

Pantheon Platform is the WebOps platform for managing websites built on Drupal and WordPress. The company focuses on empowering developers, IT professionals, and marketers to develop, test, and release website changes quickly and reliably, thereby enhancing the management of single or multiple websites. With its cloud-native software, Pantheon aims to help organizations create value through efficient website operations.

📋 Description

• Extend the configuration-driven data platform to surface data insights in the Product experience and power Machine Learning and LLM-driven insights • Serve as lead technical member of the Data Platform team and enhance Ingest, Curation, and Retention as a Service • Work hands-on with Snowflake, Snowpark for Python, Google Cloud Platform, Airflow, Docker, and Terraform • Mentor engineers and guide high-impact project design and implementation • Own development, testing, operations, and support in a full DevOps model • Drive continuous improvement of coding, testing, deployment, and communication standards • Partner with Product, Sales, Ops, Finance, and other teams on data solutions • Participate in the Data team's on-call rotation to support infrastructure stability, reliability, and performance

🎯 Requirements

• Deep understanding of processing large-scale datasets across distributed systems, including high-throughput and low-latency design trade-offs • Ability to design, implement, and optimize scalable dimensional and normalized data models for OLAP and OLTP systems • Experience with data governance frameworks, data catalogs, and observability tooling • Experience setting technical direction, translating ambiguous requirements into architecture, and mentoring engineers • Ability to align data solutions with company-wide goals and customer value • Ability to articulate technical designs, project status, and risks to technical and non-technical stakeholders • Experience embedding automated test coverage, data validation, and idempotent design into deployment pipelines • Security-, trust-, and dependability-focused design principles, including declarative design, modularity, containers, and idempotency • 8+ years building production data systems, including large-volume pipelines, cloud databases, and real-time data events • Demonstrated technical leadership mentoring engineers and driving architecture decisions • Strong hands-on experience with Python 3 • Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, Firebolt, or Redshift • Experience with Google Cloud Platform or comparable cloud environment, containers, Kubernetes, and Terraform • Familiarity with configuration-driven pipeline design, Airflow, and CI/CD for data workflows • Experience building or supporting data infrastructure for Machine Learning and LLM applications, such as feature stores, embedding/vector pipelines, or model-ready data services • Hands-on experience using AI tools to accelerate work • Clear and open communication and a team-oriented mindset • Visa Sponsorship is not available at this time

🏖️ 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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