At ProcDNA, We are building a high-impact data and AI practice focused on life sciences. This role will own both delivery excellence and capability build-out from the ground up.
- Define and drive the enterprise data architecture vision across global client engagements, ensuring alignment with business and technology strategies.
- Design and govern cloud-native data ecosystems on AWS and Azure, emphasizing scalability, resilience, interoperability, and future-state readiness.
- Serve as the principal technology advisor to clients, translating complex business challenges into innovative data and AI architecture roadmaps.
- Establish architecture standards, reference patterns, governance frameworks, and reusable accelerators to promote consistency and accelerate adoption.
- Lead the evolution of modern data platforms, including data lakes, lakehouses, real-time analytics, and AI-ready architectures.
- Drive technology decisions, architecture reviews, and platform modernization initiatives while ensuring adherence to security, compliance, and data governance principles.
- Build and nurture a high-caliber data engineering and architecture organization, fostering technical excellence, innovation, and thought leadership.
- Partner with executive stakeholders, practice leadership, and sales teams to shape solution offerings, support strategic pursuits, and expand the firm's data and AI capabilities.
Champion emerging technologies and best practices in data, analytics, and AI, creating differentiated solutions for clients, particularly within regulated industries such as Life Sciences and Pharma.
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We are looking for
- 12–18 years of experience in designing and architecting enterprise-scale data platforms.
- Strong hands-on architecture expertise with experience building and governing production-grade cloud data ecosystems.
- Deep knowledge of AWS/Azure data services, modern data architectures, distributed systems, and integration patterns.
- Experience defining architecture standards, governance frameworks, and technology roadmaps.
- Familiarity with pharma/life sciences data domains (IQVIA, claims, CRM, MDM) is a strong advantage.
- Ability to influence senior stakeholders and act as a trusted advisor on data, analytics, and AI transformation initiatives.
- Proven experience leading architecture functions and mentoring high-performing technical teams.
- Strong thought leadership in modern data, analytics, and AI technologies.
