Why Patients Need You
Technology impacts everything we do. Pfizer's digital and 'data first' strategy focuses on implementing impactful and innovative technology solutions across all functions from research to manufacturing. Whether you are digitizing drug discovery and development, identifying solutions, or making our work easier and faster, you will be making a difference to countless lives.
What You Will Achieve
Do you want to make an impact on patient health around the world? Do you thrive in a fast-paced environment that brings together scientific, clinical, and commercial domains through engineering, data science, and AI? Then join Pfizer Digital's Artificial Intelligence, Data, and Advanced Analytics organization (AIDA) where you can leverage cutting-edge technology to inform critical business decisions and improve customer experiences for our colleagues, patients and physicians. Our collection of engineering, data science, and AI professionals are at the forefront of Pfizer's transformation into a digitally driven organization that leverages data science and AI to change patients' lives. The Data Science Industrialization team within Data Science Solutions and Initiatives is a critical driver and enabler of Pfizer's digital transformation, leading the process and engineering innovation to rapidly progress early AI and data science applications from prototypes and MVPs to full production.
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As a Data Science & AI Industrialization DevOps Manager, you will be responsible for overseeing and managing the architecture and implementation of AI solutions and reusable components, with a strong focus on incorporating DevOps practices. Your role will involve driving the seamless integration of AI applications into the production environment by implementing best practices for CI/CD, infrastructure automation, containerization, configuration management, and monitoring. Your expertise in DevOps will be essential in ensuring the scalability, reliability, and ongoing operations of AI solutions. Additionally, you will provide strategic guidance and input into the AI ecosystem and platform strategy from a DevOps perspective, fostering innovation and collaboration. Join our team and contribute to improving patient health through the application of cutting-edge technology and collaboration with a diverse group of professionals.
How You Will Achieve It
- Design, implement, and maintain infrastructure and tools for software development and deployment using IaC tools.
- Automate processes for continuous integration, delivery, and deployment (CI/CD pipeline) to ensure smooth software delivery.
- Collaborate closely with developers, testers, and operations teams to facilitate seamless software delivery.
- Monitor system health and performance, proactively identifying and resolving issues.
- Perform root cause analysis to diagnose and fix production errors.
- Implement logging and monitoring tools to gain insights into system behavior.
- Train and guide junior developers on DevOps principles, fostering their professional growth.
- Foster a collaborative learning environment within the team, promoting knowledge sharing and continuous learning.
- Communicate the value of DevOps practices and reusable components to stakeholders, highlighting their impact on business outcomes.
- Collaborate with stakeholders to understand their needs, aligning DevOps practices and reusable components with their goals.
- Continuously improve and optimize DevOps processes and workflows, leveraging feedback and lessons learned.
- Stay up to date with the latest trends in DevOps, AI, and data science, and share knowledge across the organization.
- Provide strategic input to the AI ecosystem, contributing to platform evolution and new capability development.
- Collaborate with AI development teams to integrate reusable components into production AI solutions.
- Partner with the AIDA Platforms team to enforce best practices for reusable component architecture and engineering principles.
Qualifications
Must-Have
- Bachelor's degree in computer science, information technology, software engineering, or a related field (Data Science, Computer Engineering, Computer Science, Information Systems, Engineering, or a related discipline).
- 5+ years of relevant work experience in DevOps or a related field.
- Strong scripting skills in languages like Python or Bash.
- Experience with Infrastructure as Code (IaC) tools such as Terraform, Ansible, or Chef.
- Experience working in a cloud-based analytics ecosystem (AWS, Snowflake, etc.)
- Proficiency in Git for version control of infrastructure code and application code.
- Familiarity with monitoring and observability tools such as Prometheus, Grafana, or ELK stack.
- Knowledge of infrastructure security best practices and experience with security tools.
- Experience with automated testing frameworks and tools.
- Familiarity with database technologies and SQL query optimization.
- Knowledge of serverless computing and experience with serverless platforms like AWS Lambda.
- Hands-on experience working in Agile teams, following Agile processes and practices.
- Self-directed learner with a strong desire to continuously improve coding skills.
- Highly self-motivated to deliver both independently and with strong team collaboration.
- Ability to creatively take on new challenges and work outside comfort zone.
- Strong English communication skills (written & verbal)
Nice-to-Have
- Advanced degree in Data Science, Computer Engineering, Computer Science, Information Systems, or a related discipline (preferred, but not required)
- Familiarity with monitoring and observability tools such as Prometheus, Grafana, or ELK stack.
- Knowledge of infrastructure security best practices and experience with security tools.
- Experience with automated testing frameworks and tools.
- Familiarity with database technologies and SQL query optimization.
- Knowledge of serverless computing and experience with serverless platforms like AWS Lambda.
Work Location Assignment: Flexible
EEO (Equal Employment Opportunity) & Employment Eligibility
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, or disability.
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