Lead Data Manager/SAS Programmer

Role Description

We are currently seeking a Lead Data Manager/SAS Programmer who will provide senior-level leadership, technical direction, and data management and statistical programming expertise for federally funded and commercially funded clinical research and epidemiological studies. You will be a senior member of a multidisciplinary team that includes data managers and programmers, epidemiologists, statisticians, and operations staff. You will play a critical role in establishing technical approaches and standards for the collection, management, integration, and delivery of research data across the full lifecycle of complex studies.

This position will lead the design and implementation of complex data management systems, data processing programs, and automated workflows that support clinical research and public health programs. You will provide technical oversight for study data management and programming activities, identify opportunities to improve efficiency and standardization, and guide the development of scalable solutions that support data quality, integrity, and reproducibility. This position will also serve as a senior technical resource and mentor for data management and programming staff, providing guidance on complex technical challenges and promoting consistent, high-quality practices across projects. This position offers significant opportunities for professional development, innovation, and collaboration across disciplines.

Responsibilities

• Provide senior technical leadership and oversight for data management and programming activities across clinical, observational, and epidemiologic research studies, from study start-up through database closeout.
• Lead the development of technical approaches and study data strategies, including database architecture, data workflows, data specifications, collection instruments, validation rules, data integration processes, and data delivery requirements.
• Design, develop, and oversee complex SAS programming solutions for cleaning, transforming, validating, integrating, and managing research data, including reusable and automated programming frameworks.
• Establish and oversee data quality and validation processes, including programmed data checks, data reconciliation, discrepancy resolution, QC procedures, and review of complex datasets, programs, and technical deliverables.
• Provide technical direction for the integration and reconciliation of data from multiple sources, ensuring data integrity, consistency, completeness, traceability, and appropriate documentation of data transformations and decisions.
• Oversee the development and delivery of study datasets, reports, extracts, interim data cuts, and final data deliverables, ensuring that technical solutions meet study requirements and organizational standards.
• Develop and promote standardized, scalable, and efficient data management and programming practices, including automation, reusable programming solutions, version control, documentation standards, and continuous process improvement.
• Provide technical mentorship and oversight to data management and programming staff, including reviewing technical approaches, guiding resolution of complex data issues, supporting work planning and prioritization, and promoting consistent programming and QC practices.
• Serve as a senior technical advisor and collaborator to investigators, statisticians, epidemiologists, and operations staff, translating scientific and operational requirements into effective data management and programming solutions.
• Contribute to organizational standards, processes, and best practices for research data management and programming, and ensure activities comply with study requirements, organizational SOPs, applicable regulatory and privacy requirements, and established data standards.

Qualifications

• B.S. degree in computer science, health sciences, statistics, data science, or another related field, with ten or more years of progressively responsible experience in programming and data management for health research. -OR-
• M.S. degree in computer science, health sciences, statistics, data science, or another related field, with eight or more years of progressively responsible experience in programming and data management for health research.
• Advanced SAS programming capabilities, including extensive experience with DATA and PROC steps, macro programming, data transformation and integration, complex data validation, and development of efficient, reusable, and automated programming solutions.
• Extensive experience managing complex research data, preferably within clinical, observational, epidemiologic, or other biomedical research studies, with demonstrated experience leading data management activities for complex studies.
• Expert understanding of the full research data lifecycle, including study start-up, database architecture and development, data collection, data cleaning, reconciliation, quality control, data delivery, and database closeout.
• Demonstrated ability to provide technical direction and oversight for complex data management and programming activities, including defining technical approaches, evaluating solutions, identifying risks, establishing priorities, and ensuring high-quality deliverables.
• Extensive experience integrating and reconciling data from multiple sources, with the ability to resolve complex data issues and establish approaches that maintain data integrity, traceability, scalability, and reproducibility.
• Demonstrated experience developing and implementing data quality and QC frameworks, including establishing standards, reviewing technical approaches and deliverables, and identifying opportunities to improve data quality and operational efficiency.
• Excellent leadership, communication, collaboration, and mentoring skills, with the ability to provide technical guidance to data management and programming staff and effectively communicate complex technical concepts to multidisciplinary teams and senior stakeholders.
• Familiarity with clinical research data standards and regulations, such as NIH Common Data Elements, CDISC, OMOP, HIPAA, 21 CFR Part 11, GCP, and FAIR principles.
• Experience with two or more of the following is highly desirable: R, Python, SQL, database architecture and development, Git or other version control systems, APIs, and other tools used to develop efficient, scalable, and automated research data workflows.

Benefits

• Personal Time Off (PTO)
• Medical, dental, vision
• Supplemental life with AD&D
• Short and long-term disability
• Flexible spending accounts
• Parental leave
• Legal services
• 401(k) Retirement Plan with matching component
• Access to best-in-class e-learning suite for formal and informal learning
• Professional and technical certification preparation
• Education assistance at accredited institutions