Lead - Enterprise Architecture, Data & Analytics

Job Description

KEY RESPONSIBILITIES

We are seeking a highly experienced Enterprise Architecture, Data & Analytics leader to lead the strategic implementation of architecture, data, analytics, and automation capabilities. The ideal candidate will have a minimum of 20 years of experience in setting up and scaling Data & Analytics Centers of Excellence (CoE), with deep expertise in Cloud, and enterprise platforms. The role requires hands-on experience in Data, Analytics, and AI domains. Strong leadership, strategic thinking, and exceptional communication skills are essential to manage stakeholder expectations and drive innovation across business and technology.

More specifically you will have the following responsibilities:

Strategic Architecture & Planning

- Define and implement enterprise-wide Data Strategy, Analytics Strategy, and AI Strategy aligned with business objectives.
- Lead the setup and maturity of the Data & Analytics CoE, ensuring scalability, agility, and innovation.

Data Lake Architecture

- Design and manage scalable, secure, and high-performance Data Lake environments using Azure Data Services.
- Enable seamless integration of structured and unstructured data sources for analytics and data science use cases.

Data Management & Governance

- Establish and oversee enterprise-wide data management practices including data lifecycle, metadata, and master data management.
- Implement robust data governance frameworks and ensure compliance with regulatory standards (e.g., GxP, GDPR).
- Drive initiatives to improve data quality, consistency, and accessibility across systems.

Analytics & Data Science

- Architect and enable advanced analytics platforms supporting BI, predictive modeling, and data science.
- Collaborate with data owners and analysts to operationalize analytics and insights.
- Promote data-driven decision-making across business units.

AI & GenAI Enablement

- Lead the adoption and integration of AI/ML and Generative AI (GenAI) technologies to enhance business capabilities.
- Define governance and ethical frameworks for responsible AI usage.

Automation & Innovation

- Drive enterprise-wide Robotic Process Automation (RPA) initiatives to streamline operations and improve efficiency.
- Identify opportunities for automation and AI-driven transformation across the enterprise.

Enterprise Systems Integration

- Provide architectural oversight for CRM platforms (e.g., Salesforce, Veeva CRM) and ensure seamless data integration.
- Collaborate with finance teams to align data architecture with financial accounting systems (e.g., SAP).
- Support and guide web design initiatives and ensure alignment with enterprise data strategies.
- Lead and support .NET application development efforts, ensuring integration with data platforms and business logic.

Stakeholder Engagement

- Collaborate with business units, IT teams, and executive leadership to align data initiatives.
- Communicate complex technical concepts clearly to non-technical stakeholders.

Team Development & Mentorship

- Provide technical leadership and mentorship to data architects, engineers, and analysts.
- Promote a culture of innovation, collaboration, and continuous learning.

YEAR ONE CRITICAL SUCCESS FACTORS

- Successfully complete project implementations within time, cost and quality standards, in line with business and IT expectations
- Successfully complete implementation of various data integration initiatives
- Successfully develop capabilities that ensure data accuracy, integrity and accessibility

PROFESSIONAL EXPERIENCE / QUALIFICATIONS

- Bachelors or Masters degree in in Computer Science or Engineering OR equivalent years of work experience
- 20+ years of proven experience in architecting and implementing enterprise data architecture, data-lake, Data warehouse platforms, Master data Management, and analytics solutions
- Proven experience in establishing and leading Global Data & Analytics CoEs.
- Demonstrated leadership in Data, Analytics, and AI strategy.
- Strong knowledge of industry best practices around data architecture in both cloud-based and on-premises data solutions
- Exceptional understanding of building solution architectures, design patterns, network topology and data security frameworks
- Proven ability to manage stakeholder expectations effectively.
- Excellent verbal and written English skills
- Proven experience in life sciences or other regulated industries
- Excellent problem solving and data modelling skills (logical, physical, sematic and integration models)
- Familiarity with RPA tools (e.g., UiPath, Automation Anywhere).
- Experience with CRM systems, financial accounting platforms, web design, and .NET application development.
- Prior experience working with Middleware platforms like Mulesoft
- Experience with stream processing tools (Spark structured streaming, Azure Stream Analytics, Storm, etc.)
- Familiarity with Agile / Scrum methodologies

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