IT Data Architect

Position Summary  

The Data Architect plays a pivotal role in shaping and driving the evolution of our global biopharmaceutical lab network's data landscape. This position is responsible for designing and implementing data strategies, frameworks, and pipelines that enable the seamless capture, integration, and utilization of scientific and operational data across a diverse range of laboratory instruments and platforms. The Data Architect ensures that our data architecture vision is strategically aligned with the organization's scientific and business objectives, supporting the advancement of research, development, and innovation. This leader will provide operational oversight for all data architecture initiatives, including developing long-term roadmaps, managing cross-functional collaboration, and establishing governance structures that uphold data quality, security, and compliance. The Data Architect will also drive the adoption of best practices by partnering with stakeholders across research, business, and technology domains, and by facilitating the resolution of complex data challenges. Through proactive engagement and clear communication, this role will deliver regular updates on the data architecture portfolio to executive and departmental leadership, ensuring transparency and alignment as we transform data into actionable insights and strategic value. 

This position will be based in RTP, NC or Philadelphia, PA and will report to the Associate Director, IT Infrastructure. 

Job Responsibilities 

Strategy & Planning  

• Develop and deliver long-term strategic goals for the company's data architecture vision, creating a multi-year roadmap that aligns with scientific and business objectives  

• Establish and govern the processes for identifying, collecting, and managing corporate metadata. Implement methods for tracking and improving data quality, completeness, and lineage across systems 

• Create and enforce strategies for data security, backup, disaster recovery, and archiving, ensuring all data architectures and platforms follow relevant regulatory standards (e.g., GxP, 21 CFR Part 11)  

Operational Management  

• Act as the primary advocate for data management best practices, collaborating with project managers, scientific leaders, and business units on all projects involving enterprise data  

• Collaborate closely with business leaders and scientific teams to understand data needs and priorities, translating these into actionable technical requirements  

• Address complex data-related challenges, including systems integration, multi-platform compatibility, and data source mapping to ensure quality and consistency 

• Document the data architecture and environment to maintain a current and accurate view of the enterprise data landscape, enabling better decision-making and impact analysis  

Project Based Work  

• Develop robust, secure, and scalable architectures for capturing, storing, and managing laboratory data from instruments across global sites  

• Establish and maintain efficient pipelines and interfaces for seamless data movement between instruments, labs, and central data repositories  

Standardization & Governance  

• Develop and implement global standards for data structure, quality, and security, ensuring consistency across all lab environments  

• Identify opportunities to optimize data usage, introducing analytics platforms and visualizations that enable better decisions, increased efficiency, and scientific breakthroughs  

• Stay current with industry trends, new technologies, and best practices for laboratory data integration, proposing and implementing forward-looking solutions 

Minimum Requirements  

• Bachelor's degree in computer science, information technology, or related field and 8+ years of relevant work experience OR Master’s degree in computer science, information technology, or related field and 6+ years of relevant work experience 

• 6+ years of experience in data architecture, data engineering, or related roles  

• Proven hands-on experience with enterprise data modeling (conceptual, logical, physical) and business requirements analysis  

• Strong understanding of metadata management principles and tools  

• Experience with data processing flowcharting and life cycle methodologies 

• Experience within the pharmaceutical, biotech, or scientific industries  

• Expertise in data modeling, database design, and data warehouse/lake architecture (on-prem, cloud, or hybrid)  

• Experience with modern data platforms (AWS, Azure, GCP)  

• Excellent communication and stakeholder engagement skills with proven ability to align technical capabilities with business objectives  

• Strong analytical and problem-solving abilities 

Preferred Education, Experience and Skills 

• Experience with repository-based tools  

• Forward-looking mindset and ability to stay current with emerging technologies  

• Programming skills in Python, Java, or equivalent languages  

• Track record of successful cross-functional collaboration and leadership  

• Understanding of laboratory instrumentation, LIMS, ELN, and related data standards and protocols  

• Experience with regulatory compliance requirements (GxP, 21 CFR Part 11)  

• Experience developing and implementing data governance frameworks