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.
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.
Skills: data engineering,client delivery,lifescience
