Data Engineering Manager

About Redwood Materials Redwood is localizing a global battery supply chain that seamlessly integrates recovery, reuse, and recycling – keeping critical minerals in circulation and driving the energy transition. Founded in 2017, Redwood delivers low‑cost, large‑scale energy storage and produces battery materials in the U.S. for the first time, all from batteries we already have. Data Engineering Manager Responsibilities Lead and grow a team of data engineers and analysts, including hiring, mentoring, career development, and performance management. Own the long‑term roadmap and prioritization for the data platform, balancing infrastructure investment, new pipeline development, and analytics requests from across the business. Drive cross‑functional collaboration with teams across Redwood to discover needs, scope problems, and translate requirements into technical deliverables. Oversee the design and operation of data pipelines spanning streaming datasets, APIs, and various data stores, ensuring they meet reliability and quality standards. Operationalize the team – set on‑call expectations, triage incoming work, and ensure production data workloads have appropriate monitoring and incident response. Stay technically hands‑on – review code, prototype solutions, and step into pipeline or infrastructure work alongside the team. Foster a culture of technical excellence and execution, and champion the data team’s work across the broader organization. Desired Qualifications Bachelor’s degree in Computer Science, a similar technical field of study, or equivalent practical experience. Minimum 5 years of hands‑on experience building data solutions in a modern cloud environment, with at least 2 years managing technical teams. Strong technical foundation in Python and SQL sufficient to review code, evaluate design decisions, and guide the team through hard technical problems (Trino experience a plus). Familiarity with the modern data engineering stack – relational and non‑relational data stores, ELT orchestration, transformation tooling, and data observability/catalog tooling. Experience operating data platforms in AWS using infrastructure‑as‑code methodologies (CDK a plus); familiarity with containerized workloads in Kubernetes nice to have. Demonstrated ability to manage production data workloads at scale (detecting and diagnosing issues, monitoring, incident response). Strong interpersonal and communication skills; able to translate between business stakeholders and technical teams, and to advocate for the team’s roadmap with senior leadership. Physical Requirements Constantly perform desk‑based computer tasks; grasp lightly or perform fine manipulation. Occasionally stand, walk, twist, bend, stoop, or squat; reach or work above shoulders; sort or file paperwork or parts; lift, carry, push, or pull objects that weigh up to 10 pounds. Working Conditions Infrequent night/weekend work if production systems are down and require immediate attention. Benefits & Compensation The position is full‑time. Compensation will be commensurate with experience. #J-18808-Ljbffr