Description
**Role Description:**
**This Senior Manager is accountable for strategic and operational leadership of multiple Managers, Clinical Data Management Support (and their teams of Data Management Associates and Senior Associates), ensuring consistent, high-quality execution of centralized Data Management support across the portfolio.**
**This role is accountable for aligning support capacity with portfolio priorities and establishing the processes, culture, and cadence required to forecast demand, identify risks early, and respond to shifting study needs. Further, this Sr Manager role is accountable for enabling and equipping managers to lead effectively, including consistent performance standards, development pathways, and a culture of operational excellence and continuous improvement.**
**Roles & Responsibilities:**
**Team Management**
**Provide leadership, direction, and mentorship to multiple Managers, Data Management Support.**
**Set functional goals and priorities in alignment with data delivery leadership and portfolio needs.**
**Drive consistency in management practices, performance expectations, and staff development across all managers.**
**Monitor functional performance using defined metrics (capacity, quality signals, etc.) and lead corrective actions.**
**Manager Development & Support**
**Coach and develop managers’ leadership, performance management, and team building capabilities.**
**Support managers in complex performance situations, escalation handling, and sustained capacity constraints.**
**Reinforce a culture of accountability, transparency, quality, and continuous learning across the support organization.**
**Resource Planning & Program Engagement**
**Oversee resource allocation across managers’ teams to align skill and capacity to prioritized studies and timelines.**
**Anticipate resourcing risks (attrition, onboarding ramp, skill gaps, surge demand) and develop mitigation plans.**
**Partner with Talent Acquisition on hiring plans, succession planning, and workforce growth pacing.**
**Stakeholder Collaboration & Communication**
**Build strong relationships with data delivery leadership, TA leaders, and key stakeholders as the senior operational contact for escalations involving DM support teams.**
**Provide concise updates on capacity, risks, priorities, and performance to functional leadership and resourcing governance forums.**
**Quality & Compliance**
**Ensure support teams operate within SOPs, work instructions, and quality standards, with consistent documentation discipline and inspection readiness.**
**Drive corrective action when recurring quality issues or rework patterns appear.**
**Capability Building & Continuous Improvement**
**Identify skill gaps across the support workforce and build an integrated capability strategy with peers**
**Lead improvements to processes, tools, and working practices that increase consistency, efficiency, and quality of DM execution support.**
**Resource Management Support**
**Provide support to the Resource Management team as needed, including hiring coordination, allocation governance, and forecasting inputs for in-scope DM roles.**
**Basic Qualifications and Experience:**
**Doctorate degree and 12+ years of clinical data management / clinical data operations experience supporting interventional clinical trials OR**
**Master’s degree and 12+ years of clinical data management / clinical data operations experience supporting interventional clinical trials OR**
**Bachelor’s degree and 12+ years of clinical data management / clinical data operations experience supporting interventional clinical trials**
**In addition to meeting at least one of the above requirements, you must have a minimum of 4+ years experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation or resources. Your managerial experience may run concurrently with the required technical experience referenced above.**
**Preferred Experience:**
**10+ years work experience in the life sciences industry, particularly focused on clinical data management / clinical data operations for interventional clinical trials, including 5 years of biopharmaceutical clinical research experience obtained at a biotech or pharmaceutical company.**
**Experience managing multiple teams / direct reports across multiple clinical functions and ideally teams that are supporting data management delivery.**
**Clinical trial processes and operations understanding preferred, with experience in clinical data management or clinical data operations strongly preferred.**
**Proficient in Excel and collaboration tools; familiarity with common Data Management platforms and workflows (e.g., EDC such as Medidata Rave or Veeva Vault EDC, issue/query workflows, data review/reconciliation concepts) preferred.**
**Functional Competencies:**
**Must-Have Competencies:**
**Ability to lead, mentor, and develop managers and Data Management support staff across geographies while driving consistent execution and performance standards**
**Strong collaboration and communication skills to engage Data Delivery Leads, TA leaders, functional leadership, and cross-functional partners; able to manage escalations crisply**
**Deep understanding of clinical data management and clinical data operations, including database build oversight, external data acquisition, reconciliation, discrepancy management, and closeout readiness**
**Ability to detect operational and quality risks using data and trend signals (capacity strain, backlog growth, rework drivers, error patterns) and implement practical mitigation plans**
**Strong quality and inspection readiness mindset, including documentation discipline, traceability, and ensuring work is performed to SOP/WI expectations**
**Proven ability to build and scale execution teams through standard work, training frameworks, playbooks, and measurable performance management**
**Ability to operate effectively across time zones with clear handoffs, asynchronous workflows, and disciplined communication norms**
**Continuous improvement orientation focused on simplifying work, improving throughput, and reducing variability without adding bureaucracy**
