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Databricks

Builds cloud software for data analysis and AI

Manager, Delivery Solutions Architect - Healthcare & Life Sciences, HLS

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeUnited States

About the Job

Requirements

  • At least 8 years of experience in customer-facing technical roles such as Architecture, Field Engineering, or Consulting, including at least 3 years leading or managing technical teams.
  • Demonstrated success enabling production workloads in regulated industries, ideally healthcare and life sciences, life sciences, or similar GxP- or HIPAA-regulated environments.
  • Deep knowledge of cloud-native Lakehouse architectures, data governance, secure machine learning operations, and enterprise migration and modernization patterns.
  • Hands-on expertise in SQL, Python or Scala, distributed data systems, code reviews, and solution architecture.
  • A strong track record guiding customers through ETL modernization, analytics, real-time and streaming systems, and AI/ML productionization.
  • Experience with AWS, Azure, or GCP, including IAM, network security, compliance controls, and data perimeter models.
  • Ability to manage escalations, forecast usage growth, operationalize delivery frameworks, and guide cross-functional teams.
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • Willingness to travel up to 30%.

Responsibilities

  • Lead a team of Delivery Solutions Architects supporting the Healthcare & Life Sciences segment, defining strategy, setting execution rhythms, and coaching the team through long implementation cycles, compliance requirements, and enterprise programs.
  • Hire, develop, and inspire Delivery Solutions Architects who can navigate clinical, scientific, and operational workloads, and establish a performance culture focused on accuracy, velocity, and architectural excellence.
  • Guide the team to minimize onboarding friction, remove blockers, and bring healthcare and life sciences use cases—including clinical analytics, real-world evidence, supply-chain intelligence, quality systems, and AI/ML—into production quickly and safely.
  • Ensure the team maintains expertise in the Data Intelligence Platform and healthcare and life sciences requirements, including PHI-compliant architectures, HIPAA/GxP controls, auditability, lineage, and secure machine learning and AI operations.
  • Collaborate with Sales, Solutions Architects, Support, Emerging Technologies, and Professional Services to drive adoption, increase MAU/WAU, enable mature operational patterns, and help customers realize business value from Databricks.
  • Establish forecasting mechanisms, production-readiness criteria, customer health indicators, and consumption execution frameworks for predictable, multi-account delivery across healthcare and life sciences programs.
  • Engage IT, security, clinical, research and development, and data executives to shape modernization roadmaps, influence architectural direction, mitigate risk, and sponsor the strategic value of Lakehouse and generative AI.
  • Contribute to cross-business-unit initiatives that improve delivery quality, reproducibility, and reuse, including patterns, accelerators, reference architectures, and playbooks tailored for healthcare, biopharma, and payer/provider operations.

Desired Qualifications

  • Experience enabling production workloads in healthcare and life sciences, life sciences, or similar GxP- or HIPAA-regulated environments.

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size
10,001+
Company stage
Late Stage VC
Total funding
$32.1B
Headquarters
San Francisco, CA
Founded
2013

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