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Senior Data Historian Deployment Manager
2 weeks ago
Cognizant Life Sciences Manufacturing is seeking a highly skilled and experienced Technical Project Manager to lead our global Data Historian deployment project. The successful candidate will have extensive project management experience in the pharmaceutical industry, ideally using both waterfall and agile methodologies.
ResponsibilitiesThe Technical Project Manager will be responsible for managing the overall technical delivery of the project, including project planning, budget and cost management, resource allocation, stakeholder communication, risk management, quality assurance, and vendor management.
Key Responsibilities:
- Develop Detailed Project Plans: Create and maintain detailed project plans, schedules, and task coordination to ensure timely delivery.
- Manage Budgets and Costs: Oversee project budgets, track expenses, and manage cost changes to stay within financial constraints.
- Lead Resource Allocation: Manage the technical project team, ensuring optimal resource allocation and utilization.
- Maintain Stakeholder Communication: Provide regular updates and manage expectations with internal and external stakeholders.
- Identify and Mitigate Risks: Identify potential risks, develop contingency plans, and implement risk mitigation strategies.
- Ensure Quality Delivery: Adhere to standards and best practices to ensure high-quality technical project delivery.
- Apply SDLC: Use the Software Development Life Cycle (SDLC) to ensure project success.
- Collaborate with Vendors: Work with vendors to ensure timely and quality delivery of project components.
- Lead Cross-Functional Teams: Foster collaboration and drive project success through effective leadership.
- Promote Continuous Improvement: Implement continuous improvement practices within the project team.
Requirements:
- Extensive project management experience in the pharmaceutical industry.
- Experience working with Aveva-PI system.
- Knowledge of regulatory requirements (e.g., FDA, GMP).
- Proficiency in data engineering concepts and best practices.
- Strong communication and stakeholder engagement skills.
- Excellent facilitation and decision-making skills.