Lead Data Manager/SAS programmer

Accountabilities:

• • Provide senior technical leadership and oversight for data management and programming activities across clinical, observational, and epidemiological research studies from study initiation through database closeout.
  • Define technical approaches and study data strategies covering database architecture, data workflows, specifications, collection instruments, validation rules, integration processes, and delivery requirements.
  • Design, develop, and oversee advanced SAS programming solutions for cleaning, transforming, validating, integrating, and managing complex research datasets.
  • Build reusable and automated programming frameworks that improve efficiency, consistency, scalability, and reproducibility across research programs.
  • Establish and oversee data quality and validation processes, including programmed checks, reconciliation, discrepancy resolution, QC procedures, and technical reviews.
  • Lead the integration and reconciliation of data from multiple sources while maintaining data integrity, completeness, traceability, consistency, and appropriate documentation.
  • Oversee the preparation and delivery of study datasets, reports, extracts, interim data cuts, and final data deliverables in accordance with study and organizational requirements.
  • Develop standardized data management and programming practices covering automation, version control, documentation, reusable solutions, and continuous process improvement.
  • Mentor and provide technical direction to data management and programming staff, including reviewing approaches, resolving complex issues, supporting prioritization, and reinforcing strong QC practices.
  • Serve as a senior technical advisor to investigators, statisticians, epidemiologists, and operations teams, translating scientific and operational needs into effective data solutions.
  • Contribute to organizational standards, SOPs, and best practices for research data management and programming while ensuring compliance with applicable study, regulatory, privacy, and data standards.

  Requirements:

  • Bachelor’s degree in Computer Science, Health Sciences, Statistics, Data Science, or a related field with 10+ years of progressively responsible experience in programming and data management for health research; alternatively, a relevant master’s degree with 8+ years of experience.
  • Advanced SAS programming expertise, including extensive experience with DATA and PROC steps, macro programming, data transformation and integration, complex validation, and automated or reusable programming solutions.
  • Extensive experience managing complex research data, preferably within clinical, observational, epidemiological, biomedical, or public health studies.
  • Expert understanding of the complete research data lifecycle, including study start-up, database architecture, data collection, cleaning, reconciliation, QC, delivery, and closeout.
  • Demonstrated ability to provide technical leadership for complex data management and programming initiatives, including defining approaches, evaluating solutions, identifying risks, prioritizing work, and ensuring high-quality deliverables.
  • Strong experience integrating and reconciling data from multiple sources while maintaining data integrity, traceability, scalability, and reproducibility.
  • Proven experience designing and implementing data quality and QC frameworks and identifying opportunities to improve quality and operational efficiency.
  • Excellent leadership, communication, collaboration, and mentoring abilities, with the capacity to explain complex technical concepts to multidisciplinary teams and senior stakeholders.
  • Familiarity with research data standards and regulatory frameworks such as NIH Common Data Elements, CDISC, OMOP, HIPAA, 21 CFR Part 11, GCP, and FAIR principles.
  • Experience with at least two of the following is highly desirable: R, Python, SQL, database architecture and development, Git or other version control systems, APIs, and research workflow automation tools.
  • Strong analytical and problem-solving skills, with the ability to work independently and provide sound technical judgment across complex research environments.
  • Experience developing scalable, well-documented, and reproducible data workflows is strongly valued.

  Benefits:

  • $130,000–$175,000 USD annual base salary, with final compensation determined by experience, skills, geographic location, market conditions, and internal equity.
  • Potential additional performance incentives and program-specific awards.
  • Remote work opportunity.
  • Medical, dental, and vision insurance.
  • Supplemental life insurance with AD&D coverage.
  • Short- and long-term disability benefits.
  • Paid time off and parental leave.
  • Flexible Spending Accounts.
  • Legal services benefits.
  • 401(k) retirement plan with company matching.
  • Career development and professional training opportunities.
  • Access to an e-learning platform for formal and informal development.
  • Professional and technical certification preparation.
  • Education assistance for eligible accredited programs.
  • Commitment to reasonable workplace accommodations and equal employment opportunities.