What are the responsibilities and job description for the Engineering Manager / Remote position at Motion Recruitment?
The role
The Engineering Manager owns the day-to-day delivery of Mirion's Data Platform team: a small, mixed-discipline group of platform engineers, data engineers, and data warehouse engineers building cloud infrastructure, CI/CD tooling, data pipelines, and data warehouse solutions on Databricks and Azure.
This is a hands-on management role. You run sprints, review pull requests, unblock engineers, and keep delivery on track. You are not setting strategy from a distance. You are in the code reviews, the standups, and the backlog every day.
You must be technical enough to guide infrastructure and DevOps work directly, and broad enough to support data engineers when they need it. You'll coordinate with a Sr. Manager on priorities and technical direction, but the team's execution is yours.
About The Team
Mirion Technologies is a global leader in radiation safety, science, and medicine — harnessing ionizing radiation for the greater good of humanity. Our products span nuclear energy, nuclear medicine, dosimetry, defense, and cancer care, and our sensors are installed in over 90% of operating nuclear power plants worldwide. Mirion built the crew active dosimeters that protected astronauts on NASA's Artemis II lunar mission.
Mirion is growing: $925M in FY2025 revenue, record orders exceeding $1.1B, and 22–24% guided revenue growth for 2026. Two recent acquisitions — Paragon Energy Solutions (nuclear power services) and Sertrek (regulatory compliance SaaS with 15 TB of licensing data) — expand both our market position and our data and AI opportunity. The company hired its first Chief AI and Digital Officer in late 2025 with a mandate and multi-year commitment from leadership to build out data and AI capabilities company-wide.
The Enterprise Data and AI Platform team is the foundation of that initiative. We're building a centralized data platform from scratch — called MEDIAN — combining reusable, self-service tooling from Platform Engineering with the technical depth of Data Engineering. Databricks on Azure, Delta Lake, Unity Catalog, GitHub Actions for CI/CD. You'd be joining early enough to shape how things are built, with startup-level ownership inside a company with real revenue, real customers, and a 70-year history in a regulated industry that's never had a modern data platform.
About You
You've built something from scratch before, or at least been close enough to the ground floor to know what it takes. You're comfortable taking on technical debt to ship, but you take it on deliberately: you know which shortcuts will cost you a little and which ones will cost you too much, and on what time horizon. You think about where the architecture needs to go even when you're solving today's problem with today's constraints.
You communicate clearly: with your team, with your manager, and with stakeholders who don't share your technical vocabulary. You give direct, specific feedback to your engineers and you welcome it in return. You don't wait for a performance review cycle to tell someone what they need to hear.
You get energy from learning things you don't already know. This team spans infrastructure, data engineering, and data warehousing. You won't be an expert in all of it on day one, and that's fine. You care about the work this platform enables: giving engineers across a global company their first real self-service data platform.
Responsibilities
The Engineering Manager owns the day-to-day delivery of Mirion's Data Platform team: a small, mixed-discipline group of platform engineers, data engineers, and data warehouse engineers building cloud infrastructure, CI/CD tooling, data pipelines, and data warehouse solutions on Databricks and Azure.
This is a hands-on management role. You run sprints, review pull requests, unblock engineers, and keep delivery on track. You are not setting strategy from a distance. You are in the code reviews, the standups, and the backlog every day.
You must be technical enough to guide infrastructure and DevOps work directly, and broad enough to support data engineers when they need it. You'll coordinate with a Sr. Manager on priorities and technical direction, but the team's execution is yours.
About The Team
Mirion Technologies is a global leader in radiation safety, science, and medicine — harnessing ionizing radiation for the greater good of humanity. Our products span nuclear energy, nuclear medicine, dosimetry, defense, and cancer care, and our sensors are installed in over 90% of operating nuclear power plants worldwide. Mirion built the crew active dosimeters that protected astronauts on NASA's Artemis II lunar mission.
Mirion is growing: $925M in FY2025 revenue, record orders exceeding $1.1B, and 22–24% guided revenue growth for 2026. Two recent acquisitions — Paragon Energy Solutions (nuclear power services) and Sertrek (regulatory compliance SaaS with 15 TB of licensing data) — expand both our market position and our data and AI opportunity. The company hired its first Chief AI and Digital Officer in late 2025 with a mandate and multi-year commitment from leadership to build out data and AI capabilities company-wide.
The Enterprise Data and AI Platform team is the foundation of that initiative. We're building a centralized data platform from scratch — called MEDIAN — combining reusable, self-service tooling from Platform Engineering with the technical depth of Data Engineering. Databricks on Azure, Delta Lake, Unity Catalog, GitHub Actions for CI/CD. You'd be joining early enough to shape how things are built, with startup-level ownership inside a company with real revenue, real customers, and a 70-year history in a regulated industry that's never had a modern data platform.
About You
You've built something from scratch before, or at least been close enough to the ground floor to know what it takes. You're comfortable taking on technical debt to ship, but you take it on deliberately: you know which shortcuts will cost you a little and which ones will cost you too much, and on what time horizon. You think about where the architecture needs to go even when you're solving today's problem with today's constraints.
You communicate clearly: with your team, with your manager, and with stakeholders who don't share your technical vocabulary. You give direct, specific feedback to your engineers and you welcome it in return. You don't wait for a performance review cycle to tell someone what they need to hear.
You get energy from learning things you don't already know. This team spans infrastructure, data engineering, and data warehousing. You won't be an expert in all of it on day one, and that's fine. You care about the work this platform enables: giving engineers across a global company their first real self-service data platform.
Responsibilities
- Manage the Data Platform team (growing up to ~6 engineers), consisting of platform engineers, data engineers, and data warehouse engineers
- Own day-to-day engineering processes, including project planning, tracking, and delivery
- Provide hands-on technical guidance and code review for infrastructure and data engineering work
- Mentor engineers across experience levels, driving career growth and skill development
- Coordinate with Sr. Manager on technical direction and priorities
- Maintain platform reliability, observability, and operational health
- Strong technical background in cloud infrastructure on a major cloud provider (we use Azure), Terraform, and CI/CD; this is the team's primary technical surface area
- Experience managing software engineers (in any domain), leading a team of at least 4 engineers
- Comfort with hands-on, day-to-day engineering management: sprint planning, backlog grooming, PR reviews, and Jira
- Willingness and commitment to learn new fields of engineering, if you do not have both Data Engineering and Platform Engineering experience
- Experience managing platform, infrastructure, and data engineering teams specifically
- Hands-on experience with Databricks administration and development
- Familiarity with data engineering concepts (Python, Spark, SQL, data pipelines) sufficient to review work and guide data engineers
- Background building internal developer tools, templates, or self-service platforms
- Familiarity with data governance, data catalogs, data quality, and related disciplines
- Experience with observability and monitoring tools (Datadog, New Relic, Prometheus, Elastic, etc.)