We’re looking for a Senior Engineering Manager to lead Scientific Data Engineers (SDE) spread across multiple forward deployed engineering squads and drive both technical and organizational excellence. This role is ideal for a leader who can zoom out to see systemic inefficiencies across teams and processes, then roll up their sleeves to fix them — while also building a culture where engineers do their best work Supervise and guide SDEs in each squad in planning, implementation, testing, and documentation. Foster a culture of accountability, collaboration, and continuous improvement across teams Lead by example - comfortable with diving deeper into organizational and technical challenges and help the team navigate ambiguity and vagueness Manage performance, career development, and org design as teams scale Hire, mentor, and retain strong engineering talent; build a pipeline of future technical leaders Proactively identify inefficiencies in engineering workflows, processes, and cross-team handoffs — don’t wait to be told something is broken Design and implement systems (planning cadences, metrics, tooling) that increase velocity and reduce friction across teams Establish and track meaningful engineering metrics (cycle time, deployment frequency, incident rates, etc.) to guide decisions Drive continuous process improvement, balancing speed with sustainability Set and uphold engineering standards for code quality, architecture, testing, and operational reliability across teams Partner with tech leads and architects on key technical decisions and trade-offs Champion best practices in system design, scalability, and maintainability Stay close enough to the technical details to ask sharp questions and unblock teams when needed Translate company and product strategy into actionable engineering roadmaps across multiple teams Partner closely with Product, Design, and other stakeholders to align priorities and timelines Communicate progress, risks, and trade-offs clearly to executive leadership Own budget, headcount planning, and resource allocation for your organization What Success Looks Like in the First Year: Identify key engineering operational bottlenecks and inefficiencies Engineering teams operate with clear, well-understood processes and reduced cross-team friction Engineering teams able to accurately predict engineering effort and deliver high-quality products on time Measurable improvement in key engineering metrics (velocity, quality, reliability) Engineering is seen as a trusted, proactive partner by Product and executive leadership Benefits Unlimited PTO 100% Company Paid Health, Dental
Senior Manager of Scientific Data Engineering employer: TetraScience, Inc.
TetraScience, Inc. is an exceptional employer that fosters a remote-first work culture, allowing you to balance your professional and personal life while contributing to groundbreaking advancements in Scientific AI. With a strong emphasis on employee growth, TetraScience offers opportunities for continuous learning and development, alongside the chance to engage directly with clients and tackle real-world scientific data challenges. Join a team that values innovation and collaboration, where your contributions will have a meaningful impact in the biopharma industry.
