Staff Software Engineer - Data Platform

About Nimbus Data Systems Nimbus Data Systems 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. Nimbus Data Systems ’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 Nimbus Data Systems ’s collaborative workflows. The Role The Data Platform team powers Nimbus Data Systems ’s data infrastructure and delivers analytics across the company. We’ve built a robust, configuration-driven data platform that handles extraction, ingestion, curation, compliance, security, and enterprise-wide access to data — and we’re looking for a Staff Software Engineer to take it to the next level. In this role, you’ll extend the platform beyond its current foundation to surface data insights directly within our Product experience, and to power the infrastructure behind Machine Learning and LLM-driven insights. As the lead technical member of the Data Platform team, you’ll architect the next generation of services that let every team at Nimbus Data Systems trust and act on data, working closely with Software Engineers, Data Engineers, Analytic Engineers and Product. The platform runs on Python, Airflow, Kubernetes, configuration YAML, Great Expectations, and Terraform. Nimbus Data Systems ’s core values are Trust, Teamwork, Passion, and Customers First. Within engineering, we value collaboration, character, autonomy, and a no-blame culture — and we’re active participants in several open-source communities. What You Will 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 (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 Nimbus Data Systems . Support reliability. Participate in the Data team’s on-call rotation, contributing to the stability, reliability, and performance of Nimbus Data Systems ’s data infrastructure. What You Will Need to Succeed 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. What You Bring to the Table Experience: 8+ years building production data systems, with deep expertise in large-volume data pipelines, cloud databases, and real-time data events.