Solution Architect

Merck Merck · Pharma · Central Bohemian, Czech Republic

Solution Architect role focused on designing and evaluating enterprise-level architectures for Data & Analytics, Intelligent Automation, and AI, including GenAI and machine learning lifecycles. The role involves collaborating with teams, monitoring trends, and ensuring seamless integration and compliance within a regulated healthcare environment.

What you'd actually do

  1. Design and evaluate scalable solution architectures that meet enterprise needs across Data & Analytics (DnA), Intelligent Automation (IA), and AI domains.
  2. Analyze current architectures to identify gaps and recommend improvements for scalability, performance, and cost efficiency, while defining and evolving target-state architectures for DnA and IA platforms across business functions.
  3. Collaborate with developers, product owners, and architects to ensure seamless integration and compliance, while championing governance practices, applying architectural frameworks, and driving innovative solutions.
  4. Monitor industry and technology trends to shape architecture roadmaps and guide adoption of emerging capabilities like GenAI and self-service analytics.
  5. Align data architecture with business strategy, advocate for user-centric design principles and manage technical debt with remediation strategies.

Skills

Required

  • solution architecture
  • systems integration
  • data modeling
  • end-to-end system design
  • Data and Analytics platforms
  • Artificial Intelligence technologies and platforms
  • Data Lakehouse architecture
  • Data quality
  • Lineage & Cataloging tools
  • cloud-native platforms (e.g., AWS, Azure)
  • CI/CD pipelines
  • observability
  • infrastructure as code
  • GenAI
  • machine learning lifecycle
  • intelligent automation platforms
  • orchestration frameworks
  • System Development Life Cycle(SDLC)
  • SOX
  • GxP
  • data privacy regulations

Nice to have

  • TOGAF
  • AI certifications
  • Data Science certifications
  • Automation certifications
  • SAP
  • ServiceNow
  • Workday
  • Life Sciences industry experience
  • GenAI architecture
  • AI / LLMOps reference architecture

What the JD emphasized

  • Deep understanding of System Development Life Cycle(SDLC), SOX, GxP, and data privacy regulations in enterprise environments

Other signals

  • design and evaluate scalable solution architectures that meet enterprise needs across Data & Analytics (DnA), Intelligent Automation (IA), and AI domains
  • Monitor industry and technology trends to shape architecture roadmaps and guide adoption of emerging capabilities like GenAI and self-service analytics
  • Familiarity with cloud-native platforms (e.g., AWS, Azure), CI/CD pipelines, observability, infrastructure as code, GenAI, machine learning lifecycle, intelligent automation platforms, and orchestration frameworks