Staff Engineer

Overview

We are seeking a Staff Engineer to join our growing team. In this role, you will serve as a technical leader responsible for designing and implementing a robust, scalable data platform that enhances our scientific capabilities and has a measurable climate impact. You will establish best practices and set technical direction for your team, partnering closely with cross-functional stakeholders to ensure the platform adapts to meet the needs of a rapidly-evolving industry.

This is a high-impact, high-ownership role for an engineer who thrives on solving complex challenges and can operate with significant autonomy while influencing the broader technical roadmap.

Responsibilities

• Lead the design, implementation, and expansion of the company's data platform, including ingestion pipelines, data warehouse/lakehouse architecture, transformation layers, and data serving infrastructure.
• Define and champion engineering standards, best practices, and architectural patterns for data infrastructure across the organization.
• Collaborate cross-functionally to understand data needs and translate them into scalable, reliable platform capabilities.
• Drive technical decisions on tooling, frameworks, and vendor selection for the data stack (e.g., orchestration, storage, transformation, observability).
• Mentor and level up engineers on the team, providing technical guidance and code review with a focus on quality and long-term maintainability.
• Proactively identify scalability, reliability, and performance bottlenecks and lead efforts to address them.
• Partner with stakeholders across engineering, data science, and business teams to ensure the platform supports current and future analytical and operational needs.
• Contribute to organizational planning and hiring, helping grow the data engineering function.

Qualifications

• Extensive experience in data engineering, platform engineering, or a related discipline, with a track record of building and scaling data infrastructure across multiple products or business domains.
• Demonstrated experience designing and implementing end-to-end data platforms, including batch and/or streaming pipelines, data warehouse or lakehouse architectures, and transformation frameworks.
• Deep expertise in at least one major cloud platform.