Software Engineer - Data Platform

Pantheon WebOps Platform powers the open web, running more than 300,000 sites in the cloud for customers including Google, Princeton, Salesloft and Doctors Without Borders. Every day, thousands of developers and marketers create, iterate, and scale WordPress and Drupal sites to reach billions of people globally. Pantheon’s multitenant, container-based platform enables organizations to manage all of their websites from a single dashboard. Organizations including Clorox and the United Nations drive results through accelerated development and real-time publishing using Pantheon’s collaborative workflows. 

The Data Platform team powers Pantheon's data infrastructure and delivers analytics across the company. We are dedicated to providing reliable, scalable, and high-performance data solutions that drive business intelligence and operational excellence across the entire company. We are currently seeking a highly motivated and experienced Software Engineer II to join our dynamic team and play a pivotal role in shaping the future of data at Pantheon.

• →Build scalable, reliable data systems while maintaining SLOs for business-critical pipelines.
• →Partner with other internal teams such as Product, Sales Ops, and Finance to deliver high-impact data solutions.
• →Support self-service tooling and a data-driven culture across Pantheon's teams.
• →Contribute to the technical strategy and operations of Pantheon's data platform.
• →Stay up-to-date with industry trends and technologies in data engineering, analytics, and modern data platforms.
• →Continuously improve our standard of engineering excellence by implementing best practices for data architecture, testing, pipeline reliability, and documentation.

• Customer/Product Focus: An understanding of the direct or indirect business value of their work, ensuring that data solutions align with company-wide goals and provide maximum impact for internal and external customers.
• Understanding of Distributed Data Systems: Familiarity with the concepts and challenges of processing large-scale datasets across distributed systems and a clear grasp of trade-offs when designing solutions for high throughput and low latency.
• Data Modeling and Architecture: The capability to design, implement, and optimize scalable data models (e.g., dimensional, normalized) for both data warehouse (OLAP) and transactional (OLTP) systems to ensure data integrity and query performance.
• Strong Written and Verbal Communication Skills: The ability to clearly articulate technical designs, project status, and potential risks to both technical peers and non-technical stakeholders (Product, Sales, Finance, etc.).
• Quality Mindset: Understanding of how to integrate automated test coverage and validation into a deployment pipeline.

• Demonstrated Experience: 3-5+ years of experience building production services and features, ideally with a mix of Data Engineering expertise.
• Coding Proficiency: Ability to build maintainable components in Python and/or Go.
• Database Knowledge: Comfortable using SQL with relational databases (e.g. MySQL, Postgres) and data warehouses (e.g. Snowflake, BigQuery).
• Cloud & Infrastructure: Experience working with containerization (e.g., Docker, OCI), Terraform, and Kubernetes (K8s).
• Data Experience: Familiarity with modern data stacks (e.g. Snowflake, dbt, Airflow, Looker)