Senior Engineering Manager, Platform Engineering & Data Systems

Carbon Mapper is a non-profit organization focused on reducing greenhouse gas emissions through accessible data. They are seeking a Senior Engineering Manager to lead a team of engineers in developing software platforms and data systems that transform satellite observations into actionable data.

Responsibilities:

• Lead and support a team of senior engineers across software platforms, data pipelines, and cloud infrastructure
• Oversee people management, including performance management, career development, and regular feedback
• Provide day-to-day guidance, remove blockers, and support engineers in delivering high-quality, reliable outputs
• Balance hands-on technical contributions to backend services, data pipelines, and AWS infrastructure with management responsibilities, focusing individual contributor time on high-impact work
• Partner with the Senior Technical Project Manager on planning, prioritization, resourcing, and execution
• Contribute to scoping, estimation, feasibility assessment, and sequencing of work
• Participate actively in sprint ceremonies and planning, partnering with the Senior Technical Project Manager who leads sprint facilitation
• Provide technical leadership on architecture and system design — including scalable, cloud-based system and data architecture — and set technical direction on cross-cutting decisions in collaboration with senior engineers
• Own the reliability, performance, and scalability of production services and data pipelines, including capacity planning, SLAs, and on-call health
• Champion secure system design and access control (e.g., IAM and data access) to protect our systems and the public data platform
• Support engineers in navigating technical tradeoffs, dependencies, and ambiguity; escalate risks as needed
• Promote consistent engineering practices across code quality, testing, documentation, CI/CD and deployment, observability, and pipeline reliability
• Identify delivery risks early and partner with stakeholders to maintain predictable execution
• Collaborate with product, science, operations, and external partners to ensure alignment and clear expectations
• Support hiring efforts and lead onboarding to enable new team members to contribute effectively
• Establish regular 1:1s and feedback mechanisms to support team effectiveness and engagement
• Foster a culture of ownership, transparency, and collaborative problem-solving
• Contribute to scalable processes that improve clarity and predictability while minimizing unnecessary overhead

Requirements:

• 8+ years of engineering management experience, including the support of senior individual contributors
• Hands-on engineering background in Python and at least one other backend language, with the ability to read, review, and contribute to production code
• Hands-on experience operating production AWS infrastructure for application, data, and platform systems — Lambda, Step Functions, ECS, AWS Batch, CloudWatch, S3, IAM, and networking
• Experience with CI/CD and deployment automation (e.g., GitLab CI, GitHub Actions, Terraform/IaC, containerized deploys) and a track record of safe, frequent releases
• Experience standing up or improving observability and reliability practices (monitoring, logging, alerting, on-call) for production services
• Applied AI engineering experience with Claude Code, Cursor, Codex, or agentic AI workflows
• Experience supporting engineers working across multiple technical domains
• Experience partnering with technical project or program managers, with clear alignment between people management and execution processes
• Demonstrated ability to identify risks, remove blockers, and support predictable delivery in a dynamic environment
• Ability to break down complex problems and support teams in navigating ambiguity
• Strong communication and interpersonal skills, with the ability to build trust and provide clear, constructive feedback
• Experience improving team effectiveness, engineering quality, and system reliability in a small or scaling organization
• Ability to collaborate effectively with engineers, scientists, and cross-functional partners
• Experience hiring and onboarding engineers in a growing technical organization
• Exposure to geospatial systems, remote sensing, or scientific computing — or strong interest in learning the domain (we'll teach the geospatial specifics)
• Experience working with large-scale data processing or production data pipelines
• Experience supporting machine learning or algorithm-driven data products in production
• Experience working in cross-disciplinary environments involving science, engineering, and operations