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Technical DevOps Lead - Life Sciences
Technical DevOps Lead - Life SciencesMcKinsey & Company • Detroit
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Technical DevOps Lead - Life Sciences

Technical DevOps Lead - Life Sciences

McKinsey & Company • Detroit
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  • [job_card.full_time]
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Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance / high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.

In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have :

  • Continuous learning :  Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • A voice that matters :  From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community :  With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World-class benefits :  On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

As the Data & Analytics CoE Tech Lead, you will make application architecture decisions with the help of the team, while leveraging GenAI-supported insights, tools, or accelerators when relevant. You will deliver highly performant, tested, and scalable clean code, with openness to incorporating GenAI-assisted development practices when beneficial. You will also own product deployment and performance in production, potentially using GenAI-based observability or anomaly detection tools in the operating environment.

In this role, you will mentor and coach the technical team, including through code reviews and pair programming, and encourage thoughtful use of GenAI tools in the development process. You will anticipate and identify technical impediments and resolve them through architecture design, technology choices, or prioritization—considering GenAI’s role in enhancing or accelerating these pathways. Additionally, you will work closely with the Product Owner to align the roadmap with strengths and opportunities within the existing architecture, including GenAI-enabled processes.

You will act as a thought partner to the Product Owner in story creation and acceptance criteria, clearly communicating tradeoffs in a GenAI-aware environment. You will co-create engineering practices, coding style guidelines, and testing approaches, embedding GenAI considerations such as code suggestions, test automation, or documentation generation where appropriate. Finally, you will constantly look for better ways to solve technical problems and design solutions, remaining open to challenging the status quo and integrating GenAI-supported methods where they enhance team performance or quality.

McKinsey’s Life Sciences (LS) Practice serves clients across multiple dedicated functional service lines spanning Commercial, R&D, and Operations, as well as a host of client interest groups and functional joint ventures. Within the LS Practice, you’ll be a member of the Data & Analytics CoE.

The Data & Analytics CoE is a highly visible, critical component of the practice. We are a growing group with an expanding global footprint. This is a top global priority and a high-profile position; the CoE regularly works with McKinsey Life Sciences senior leaders. We have the important remit of improving the insights we deliver to clients by designing the data strategy and delivering a large portion of analytics for the LS practice.

  • Bachelor’s or advanced degree from an accredited institution, with consulting experience preferred—ideally within healthcare.
  • Strong experience leading the development of large-scale applications across multiple technical stacks, with familiarity in cloud environments and DevOps practices
  • Hands-on technical expertise, with proficiency in SQL, Python, and experience in unit and end-to-end testing frameworks
  • Skilled in Agile Development methodologies, backlog prioritization, and feasibility / complexity assessments
  • Comfortable working in environments where GenAI tools support development, testing, and automation workflows, and able to guide responsible use of AI-assisted tools
  • Entrepreneurial mindset with the ability to thrive in a fast-changing environment and build connections across the organization
  • Exceptional problem-solving skills, creativity, and a passion for working in cross-cultural environments
  • Familiarity with big data, pharmaceutical / MedTech data, and a working knowledge of the pharmaceutical space a plus
  • Proven track record of leading high-performing engineering teams, mentoring and coaching team members, and fostering technical excellence
  • Balances hands-on coding with leadership, teaching best practices, and guiding technical decisions to maximize team potential
  • Strong communication skills, with the ability to align teams on complex technical decisions and explain technical concepts to non-technical colleagues
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