Manager Data Engineering

Johnson & Johnson MedTech is recruiting for a Manager Data Engineering located in Jacksonville, FL.

Caring for the world, one person at a time has inspired and united the people of Johnson & Johnson. We embrace research and science -- bringing innovative ideas, products and services to advance the health and well-being of people.

At Johnson & Johnson, we believe good health is the foundation of vibrant lives, thriving communities and forward progress. That’s why for more than 130 years, we have aimed to keep people well at every age and every stage of life. Today, as the world’s largest and most broadly-based healthcare company, we are committed to using our reach and size for good. We strive to improve access and affordability, create healthier communities, and put a healthy mind, body and environment within reach of everyone, everywhere. Every day, our more than 130,000 employees across the world are blending heart, science and ingenuity to profoundly change the trajectory of health for humanity.

This critical role is responsible for overseeing and coordinating activities related to the organization, storage, retrieval, and protection of strategic Supply Chain data assets within Johnson & Johnson Vision. The incumbent is a key digital team member and leader reporting to the Director of Digital Strategy, Analytics & Insights supporting the global Johnson & Johnson Vision Supply Chain organization and works to advance the deployment of the supply chain Common Data Layer strategy, in alignment with the Vision franchise business needs, and MedTech and Enterprise strategies.

The Data Engineering Manager will systematically power E2E digital solutions and digital use cases that improve internal efficiency, effectiveness, and experience. The role will require a balance of technical expertise as a key advisor to the business as well as a high level of supply chain domain knowledge to coordinate and translate business requirements to the strategic data assets necessary to enable the desired digital capabilities. Strong technical skills paired with leadership and supply chain business expertise are essential to success in this behind the scenes, impactful, and digitally enabling position.

Responsibilities:

1. Data Governance:

2. Establishing and enforcing data management policies and procedures.

3. Collaborating with compliance and data privacy regulation SMEs to account for their requirements into E2E data solutions where possible.

4. Developing and implementing data governance frameworks.

5. Data Quality Management:

6. Collaborating with data stewards and data owners to help them address data quality issues.

7. Cloud Infrastructure Management:

8. Overseeing the design, build, and maintenance of E2E Supply Chain data infrastructure – including databases, schema and table designs, and integration with both source systems and data consumption applications.

9. Managing E2E data models and schemas.

10. Collaborating with IT to ensure cloud resource performance and security.

11. Data Integration:

12. Facilitating the integration of data from various sources.

13. Implementing and managing ETL (Extract, Transform, Load) processes.

14. Ensuring data consistency and integrity across different systems.

15. Data Security and Privacy:

16. Implementing measures to protect sensitive data.

17. Collaborating with IT security teams to ensure data confidentiality.

18. Ensuring compliance with data protection regulations.

19. Data Analytics Support:

20. Collaborating with data analysts and data scientists to provide access to quality data.

21. Facilitating the use of data for business intelligence and analytics purposes.

22. Data Documentation:

23. Maintaining comprehensive documentation for data processes and structures.

24. Creating metadata and data dictionaries to aid understanding and use of data.

25. Data Lifecycle Management:

26. Managing the entire lifecycle of data from creation to archiving or deletion.

27. Implementing data retention policies and procedures.

28. Training and Communication:

29. Providing training to employees on data management policies and best practices.

30. Communicating changes in data management processes and policies.

31. Risk Management:

32. Collaborating with IT to identify and mitigate risks associated with data management.

33. Planning for data recovery in case of data loss or system failures.