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Clinical Data Managers

SOC 15-2051.02Job Zone 4 · Considerable Preparationv.26.05

Context coveredThis framework covers clinical data management practice across the full lifecycle of regulated clinical trials — from initial database setup and data entry through query resolution, database lock, and regulatory submission — within pharmaceutical, biotech, CRO, and academic research environments.

Sources:O*NET v30.2O*NET Resource Center — Occupational Information Network, v30.2 (Sept 2025). Opens in new tab.SkillsCrosswalkSkillsCrosswalk — O*NET enrichment + adjacency index. Opens in new tab.
Emerging
Entry / Apprentice
  1. Clinical database entry tasks — execute under direct supervision following established data entry protocols in a regulated clinical trial environment.
  2. Standard data receipt and filing procedures — apply consistently using approved electronic data capture systems on assigned study records.
  3. Basic logic check results — recognize and flag discrepancies for senior review during routine data verification activities.
  4. Pre-built data query templates — utilize to document and submit identified data omissions to the clinical data team.
  5. Standard operating procedures for data management — follow precisely to ensure compliance during initial project assignments.
  6. Existing data collection forms — interpret and populate accurately using study-specific instructions provided by senior staff.
  7. Spreadsheet and office suite software — operate to prepare basic data activity listings under guidance from a supervising data manager.
  8. Medical terminology and coding conventions — recognize and apply at a foundational level when processing clinical trial data.
  9. Data formatting specifications — implement as directed when preparing assigned data sets for downstream analytical use.
  10. Progress tracking reports — compile from provided templates to summarize routine data receipt and entry activities for team review.
Developing
Mid-level / Established
  1. Clinical database structures — design and configure with reduced oversight using validated database user interface and query software for mid-sized trial protocols.
  2. Data validation logic checks — develop and test independently to identify entry errors across assigned study databases in a GCP-compliant environment.
  3. Data queries — generate and manage in response to validation failures, resolving discrepancies by coordinating directly with clinical site staff.
  4. Project-specific data management plans — draft covering coding conventions, data transfer schedules, and database lock procedures for single-protocol studies.
  5. Routine data quality metrics — monitor and report to detect deviations from standard operating procedures across ongoing data management activities.
  6. Custom data collection forms — design and refine to support efficient receipt, processing, and tracking of clinical data across assigned trials.
  7. Analytical and categorization software — apply to prepare formatted data sets meeting sponsor or regulatory formatting requirements with minimal direction.
  8. Database lock workflows — coordinate within a study team to ensure timely completion of data cleaning and readiness for statistical analysis.
  9. Performance and progress reports — prepare independently by querying databases and summarizing data entry productivity metrics for project managers.
  10. Time management and task prioritization — exercise routinely to balance simultaneous data management responsibilities across multiple active study protocols.
Proficient
Senior / Expert IC
  1. Complex clinical database architecture — design, validate, and optimize autonomously including advanced logic checks and edit specifications for large multi-site trials.
  2. End-to-end data management plans — author and implement covering full lifecycle from data receipt through database lock, transfer, and regulatory submission.
  3. Non-routine data discrepancies — resolve independently by applying deductive and inductive reasoning to assess root cause and coordinate corrective actions across clinical and statistical teams.
  4. Cross-functional data workflows — evaluate and re-engineer using systems analysis techniques to improve efficiency and compliance in a clinical operations environment.
  5. Programming scripts and queries — develop using object-oriented or scripting tools to automate validation, cleaning, and data transformation processes.
  6. Regulatory and sponsor data standards — interpret and apply across all study deliverables, ensuring data sets conform to CDISC or equivalent frameworks.
  7. Risk-based data monitoring plans — construct and execute to proactively identify data integrity issues before database lock across complex trial portfolios.
  8. Advanced analytical listings and outputs — produce independently to support interim analyses, safety reviews, and final study reports for regulatory submissions.
  9. Vendor and CRO data management activities — oversee and quality-assure to ensure external data pipelines meet contractual and protocol-defined standards.
  10. Mentoring and technical guidance — provide to junior data managers on database design, query resolution, and SOP compliance within day-to-day project work.
Advanced
Lead / Principal / Executive
  1. Organizational data management strategy — define and lead across an enterprise clinical development portfolio, aligning practices with evolving regulatory and industry standards.
  2. Clinical data management SOPs and governance frameworks — author and maintain at the organizational level to ensure consistent, audit-ready data quality practices.
  3. Enterprise-wide database and technology infrastructure — evaluate, select, and champion including EDC platforms, analytical software, and data integration systems.
  4. Departmental competency and talent development programs — design and implement to build clinical data management capability across emerging, developing, and proficient staff.
  5. Executive and regulatory stakeholders — engage and advise on data integrity risks, database lock timelines, and data submission readiness for high-stakes regulatory filings.
  6. Cross-departmental data governance committees — lead to establish enterprise data standards, change control processes, and system validation policies.
  7. Complex problem escalations — resolve at the organizational level by applying systems evaluation and judgment to determine precedent-setting data management decisions.
  8. Innovation and continuous improvement initiatives — drive by evaluating emerging technologies such as risk-based monitoring tools and AI-assisted data cleaning platforms.
  9. Strategic partnerships with CROs, sponsors, and health authorities — negotiate and manage to align data management deliverables with organizational and regulatory objectives.
  10. Organizational performance metrics and quality dashboards — design and champion to provide leadership visibility into data management productivity, compliance, and risk indicators.

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Sources:Anthropic Economic IndexAnthropic Economic Index — release_2026_03_24. Opens in new tab.Jadhav & Danve, 2026Skill Automation Feasibility Index — Jadhav & Danve, 2026 (arXiv:2604.06906). Opens in new tab.WEF Skills TaxonomyWEF Skills Taxonomy 2021 — Building a Common Language for Skills at Work. Opens in new tab.

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Source anchors that ground each statement

Related titles
Abstractor · Analyst · Application Analyst · Application Coordinator · Clinical Applications Director · Clinical Biostatistics Director · Clinical Data Abstractor · Clinical Data Analyst · Clinical Data Coordinator · Clinical Data Management Director (CDM Director) · Clinical Data Management Manager (CDM Manager) · Clinical Data Manager
RAPIDS apprenticeships
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O*NET skills
Critical ThinkingSpeakingReading ComprehensionActive ListeningWritingActive LearningMonitoringMathematicsComplex Problem SolvingCoordinationTime ManagementSystems AnalysisProgrammingJudgment and Decision MakingSocial PerceptivenessSystems EvaluationManagement of Personnel ResourcesInstructing
Knowledge domains
English LanguageComputers and ElectronicsCustomer and Personal ServiceMathematicsMedicine and Dentistry
Abilities
Deductive ReasoningInformation OrderingOral ExpressionWritten ComprehensionOral ComprehensionNear VisionProblem SensitivityInductive ReasoningWritten ExpressionSpeech Recognition
Work styles
Attention to DetailDependabilityIntegrityCautiousnessIntellectual CuriosityAchievement Orientation
Technology
Data base user interface and query softwareMedical softwareCategorization or classification softwareObject or component oriented development softwareAccess softwareAnalytical or scientific softwareEnterprise application integration softwareDevelopment environment softwareSpreadsheet softwareOffice suite software
Tasks · seed anchors for statements
  1. Design and validate clinical databases, including designing or testing logic checks.
  2. Process clinical data, including receipt, entry, verification, or filing of information.
  3. Generate data queries, based on validation checks or errors and omissions identified during data entry, to resolve identified problems.
  4. Develop project-specific data management plans that address areas such as coding, reporting, or transfer of data, database locks, and work flow processes.
  5. Monitor work productivity or quality to ensure compliance with standard operating procedures.
  6. Prepare appropriate formatting to data sets as requested.
  7. Design forms for receiving, processing, or tracking data.
  8. Prepare data analysis listings and activity, performance, or progress reports.
CIP education codes
11.010211.010311.070111.080211.080426.110326.110426.119927.010127.030127.030327.030427.030527.030627.039927.050127.050227.050327.060127.999930.080130.300130.390130.480130.700130.709930.710130.710230.710330.710430.719940.051245.060352.130152.1302

Sources: O*NET v30.2 (CC BY 4.0), SkillsCrosswalk.com, LER.me®, Anthropic Economic Index, SAFI (Jadhav & Danve, 2026), WEF Skills Taxonomy 2021, Pathsmith™ Durable Skills Framework. © 2026 EBSCOed.