Program Manager, Databricks & Enterprise Data Platforms

Role Overview

Fractal is seeking a Program Manager to lead large-scale data, AI, and technology transformation initiatives for a leading global biopharmaceutical company based in the New Jersey region. This is a client-facing architecture role for someone who can operate at the intersection of life sciences consulting, enterprise data platforms, AI/ML enablement, and cloud-native engineering.

Key Responsibilities

• Manage multiple concurrent Databricks initiatives for a leading global biopharmaceutical company, driving delivery across internal stakeholders and vendor partners.
• Be the Client’s Trusted Advisor.
• Drive senior client workshops focused on problem framing, solution strategy, modernization roadmaps, and AI/data platform transformation.
• Serve as a trusted technical advisor to VP, Executive Director, and senior business/technology stakeholders.
• Translate business priorities and analytical needs into scalable architecture strategies, data models, platform designs, and delivery roadmaps.
• Partner with client stakeholders to identify new opportunities where AI, analytics, data engineering, and cloud platforms can drive measurable business impact.
• Help drive client success by ensuring solutions are aligned to business outcomes, enterprise standards, and long-term scalability.

Enterprise AI & Data Architecture

• Own the architecture vision for modern life sciences data and AI platforms across complex, multi-team programs.
• Define reference architectures, reusable patterns, governance models, and engineering standards for AI-ready data platforms.
• Design scalable data architectures across ingestion, transformation, modeling, metadata, lineage, quality, consumption, and observability layers.
• Guide architecture decisions across Databricks, distributed compute, data engineering, analytics, and AI/ML enablement.
• Evaluate current-state data ecosystems and define practical future-state modernization roadmaps.
• Ensure platform designs are secure, reliable, observable, cost-efficient, and aligned with enterprise architecture best practices.

AI Foundations in Life Sciences

• Lead data and platform modernization efforts that support AI foundations, governance, operational layers, context layers, and ontology-driven architectures.
• Apply life sciences domain context to platform and architecture decisions, including experience with pharma data ecosystems, modernization, migration, and analytical workloads.
• Establish standards for data modeling, metadata management, lineage, data quality, governance, and operational excellence.
• Partner with business and technical teams to design architectures that support advanced analytics, AI/ML, self-service insights, and enterprise data products.
• Ensure solutions are built to support reliability, observability, automation, and long-term adoption.

Technical Leadership & Delivery Governance

• Provide architecture leadership across onsite/offshore teams, engineering squads, data product teams, and client stakeholders.
• Review solution designs for scalability, performance, security, maintainability, and cost optimization.
• Guide technical execution across complex programs without becoming a bottleneck for delivery teams.
• Establish CI/CD, DevOps, testing, monitoring, and operational practices that support enterprise-grade platform delivery.
• Mentor architects, engineers, and technical leads on modern data platform design and AI-ready architecture patterns.
• Drive technical visioning, thought leadership, in-person workshops, and client-facing architecture discussions.

Required Experience

• Core Architecture & Consulting Experience: 7+ years of experience in data architecture, software engineering, cloud platforms, AI/ML platforms, data engineering, or enterprise solution architecture.
• Consulting, Client Advisory, or Complex Enterprise Technology Transformation Experience: 4+ years of experience.
• Life Sciences, Pharmaceutical, Healthcare, or Regulated Enterprise Data Environments Experience: Strong experience.
• Business, Technology, and Executive Stakeholders Experience: Proven ability to lead architecture across large, multi-team programs.
• Modernization Roadmaps, Future-State Architecture Models, Platform Strategies, and Technical Governance Frameworks Experience: Experience developing.
• Executive Presence and Senior Stakeholder Conversations Experience: Ability to independently lead.

Technical Depth

• Hands-On Architecture Experience with Databricks, AWS, Spark, SQL, Python, and Modern Data Engineering Practices: Strong experience.
• Cloud-Native Data Platforms, Distributed Compute, MPP Systems, Lakehouse Architectures, and Enterprise-Scale Analytical Workloads Experience: Experience with.
• Data Modeling, Metadata, Lineage, Data Quality, Governance, and Platform Observability Understanding: Strong understanding.
• Ci/CD, DevOps, Automated Testing, Monitoring, Logging, and Cost Optimization Practices Experience: Experience with.
• Familiarity with dbt Core/Cloud, Data Vault 2.0, Data Product Architecture, and Modern Data Transformation Patterns: Familiarity with.
• Ingestion, Transformation, Modeling, Semantic/Context Layers, and Consumption Layers Design Experience: Experience designing.

Life Sciences & AI Foundations Experience

• Life Sciences Data Ecosystems, Pharma Data Modernization, Migration, and Governance Experience: Experience with.
• AI Foundation Concepts Including Operational Layers, Context/Ontology Layers, Data Readiness, Governance, and Scalable Platform Enablement Understanding: Understanding of.
• Connecting Business Problems to Practical AI, Analytics, and Data Platform Solutions Experience: Experience driving.
• Enterprise Data Platforms, Modern Data Practices, and AI-Ready Engineering Standards Experience: Experience with.

Preferred Experience

• Fortune 500 or Fortune 50 Clients in Life Sciences, Healthcare, Pharma, or Regulated Industries Experience: Experience with.
• AWS Services Such as S3, Glue, Redshift, EMR, Lambda, Athena, Kinesis, DynamoDB, or Related Cloud-Native Services Experience: Experience with.
• Databricks Platform Architecture, Lakehouse Patterns, Unity Catalog, ML/AI Enablement, or Large-Scale Migration Programs Experience: Experience with.
• Thought Leadership, Solution Accelerators, Reusable Architecture Patterns, or Client-Facing Transformation Offerings Experience: Experience contributing to.
• Global Delivery Model with Onsite/Offshore Engineering and Architecture Teams Experience: Experience working in.

Pay

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: Up to $150,000. In addition, you may be eligible for a discretionary bonus for the current performance period.

Benefits

• Health, Dental, Vision, Life Insurance, and Disability Plans Eligibility: Available upon hire.
• Disability Plan Eligibility: After 30 days of employment.
• 401(k) Plan Participation: After 30 days of employment.
• 11 Paid Holidays: Available upon hire.
• 12 Weeks of Parental Leave: Available upon hire.
• Free Time PTO Policy: Available upon hire.

Equal Employment Opportunity

At Fractal, we provide equal employment opportunities to all employees and applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.