Senior Data Manager/SAS programmer

Accountabilities:

• • Lead data management activities for clinical, observational, and epidemiological research studies from study start-up through database closeout, ensuring data is complete, accurate, traceable, and fit for purpose.
  • Design, develop, and maintain study databases, data collection instruments, validation rules, data specifications, cleaning procedures, and data transfer processes.
  • Perform advanced SAS programming to clean, transform, validate, integrate, and manage complex research datasets while developing efficient, reusable, and automated programming solutions.
  • Develop and execute data quality and validation procedures, including programmed data checks, reconciliation, discrepancy resolution, and independent quality control of datasets, programs, and deliverables.
  • Integrate and reconcile data from multiple sources while documenting data transformations, decisions, and processes to maintain consistency and traceability.
  • Develop and maintain study datasets, reports, extracts, interim data cuts, and final data releases for investigators, statisticians, and other research stakeholders.
  • Lead the design and implementation of complex data processing programs and automated workflows that improve efficiency and scalability.
  • Provide technical leadership and mentorship to data management and programming staff, including work planning, risk identification, technical guidance, and promotion of consistent programming and QC practices.
  • Collaborate with multidisciplinary teams to ensure study activities comply with applicable requirements, organizational SOPs, privacy standards, regulatory expectations, and established data management practices.
  • Identify opportunities to improve data workflows, automation, quality controls, and programming standards across research programs.

  Requirements:

  • Bachelor’s degree in Computer Science, Health Sciences, or a related field with 7+ years of programming and data management experience in health research, or a master’s degree in a related field with 5+ years of relevant experience.
  • Advanced SAS programming expertise, including extensive experience with DATA and PROC steps, macro programming, data transformation and integration, complex validation, and reusable programming solutions.
  • Demonstrated experience managing complex research data, preferably within clinical, observational, epidemiological, biomedical, or public health studies.
  • Strong understanding of the complete research data lifecycle, including database development, data collection, cleaning, reconciliation, quality control, delivery, and database closeout.
  • Experience integrating and reconciling data from multiple sources and resolving complex data issues while maintaining integrity, traceability, and appropriate documentation.
  • Ability to independently lead complex data management and programming initiatives, define technical approaches, manage competing priorities, identify risks, and deliver high-quality work on schedule.
  • Strong quality assurance mindset and exceptional attention to detail, with experience developing QC procedures and independently reviewing data, code, datasets, and technical deliverables.
  • Excellent communication and collaboration skills, with the ability to explain technical concepts to multidisciplinary audiences and provide guidance to less experienced professionals.
  • Experience with additional technologies such as R, Python, SQL, database architecture and development, Git/version control, APIs, or related tools for scalable and automated data workflows is highly desirable.
  • Familiarity with clinical research data standards and regulations such as NIH Common Data Elements, HIPAA, 21 CFR Part 11, GCP, or FAIR principles is highly desirable.
  • Strong analytical, organizational, problem-solving, and project management skills, with the ability to operate effectively in a multidisciplinary research environment.

  Benefits:

  • Base salary of $110,000–$140,000 per year, with final compensation determined by experience, skills, location, market conditions, and internal equity.
  • Potential performance incentives and program-specific awards.
  • Remote work opportunity.
  • Paid Personal Time Off (PTO).
  • Medical, dental, and vision insurance.
  • Supplemental life insurance with AD&D coverage.
  • Short- and long-term disability benefits.
  • Flexible Spending Accounts (FSAs).
  • Parental leave.
  • Legal services benefits.
  • 401(k) retirement plan with employer matching.
  • Career development and professional training opportunities.
  • Access to an e-learning platform for formal and informal learning.
  • Professional and technical certification preparation.
  • Education assistance at accredited institutions.
  • Opportunities to collaborate with multidisciplinary teams working on impactful health research and public-sector programs.