AI Data Management Lead

gital Manufacturing Team provides common application platforms and solution capabilities for Digital Plant, Manufacturing Operations, Manufacturing Execution, Manufacturing Insights and Digital Quality solutions, while ensuring a unified User Centric Design. Key to the success of this transformative digital mindset is the secure, seamless flow of contextualized data from the device & control levels, all the way to the top of the Enterprise. These solutions are deployed across more than fifty manufacturing & center locations across the PGS Globally. Major Core Solutions and team capabilities for the Manufacturing Operations Solutions Team include:

• This group supports the design, development, delivery and digitization of PGS Manufacturing and Engineering processes. Process Areas (Systems) include Industrial Internet of Things, Enterprise Data Historians, Cybersecurity, Manufacturing Operations Solutions (Manufacturing Intelligence, EAMS Maintenance Mgmt & Calibration, Capital Mgmt, Permit to Work, OEE/RTE, Engineering systems), Manufacturing Execution Systems and Manufacturing Innovative Technologies including AI/ML and Generative model based digital solutions.

The AI Data Management Lead plays a key role in delivering the future of Advanced Manufacturing Capabilities within the Digital Manufacturing Organization. The colleague will be responsible for leading a team of data engineering and data analysts' experts who will deliver the AI/ML and Generative AI solutions for Digital M4.0 team. As a data management lead, the candidate will be also responsible for working with others in architecting, developing, prototyping, maintaining, and optimizing the centralized data mart and associated data pipelines and products. In addition, the candidate will support multiple stakeholders, including business owners, software engineers, database architects, data analysts, and data scientists, to ensure optimal data delivery pipelines and workflows. The ideal candidate should possess strong data understanding, analytics, and technical abilities to solve complex data problems and establish a data management process to stop avoiding it again, be willing to learn new technologies and tools when necessary and be comfortable supporting the data needs of multiple internal teams and organizations.

ROLE RESPONSIBILITIES

• Implement best practices and execute in creating data management policies, ensuring data quality, implementing secure procedures, analyzing data systems, supporting data users, and troubleshooting data-related problems.

• Formulating management techniques for quality data collection to ensure adequacy, accuracy, privacy, security, and legitimacy of data and fulfilling the data scientists and other requirements.

• Involves looking for patterns, understanding database design concepts and being able to participate in short and long-term planning about database projects.

• Maintain and optimize the data required for discovery, accurate extraction, transformation, and data loading from various sources.

• Identify gaps in existing data strategies for collecting, processing, storing, and retrieving data products from the M4.0 Data Lake. Guide the MI development teams on how to fill the gaps identified.

• Ensuring the effective use of a central database, aligning with M4.0's downstream requirements and identifying ways to use the available data to pursue business goals.

BASIC QUALIFICATIONS

• Bachelor's degree in computer science, Information Systems, or a related field.

• 8+ years of work experience in medium to large data management/architect projects

• Demonstrated hands-on experience in database management and administration, as well as data pipeline tools and technologies.

• Demonstrated experience with data management competencies and projects.

• Strong interpersonal skills and evidence of enabling teamwork in a matrix environment.

• Proven ability to build coalitions and develop strong partnerships across functions.

PREFERRED QUALIFICATIONS

• Advanced SQL skills and experience with relational databases and database design.

• Experience working with Cloud Data Warehouse solutions in Snowflake, Python, MySQL, Commercial databases, and Timeseries DB.

• Experience working with data ingestion/ETL tools like IICS, HVR, Tibco BW, Streambase, DS, Databricks, Data IKU, Collibra, AWS Glue, and other AWS services.

• Working knowledge of AWS Cloud-based solutions.

• Strong proficiency in data pipeline and workflow management tools.

Work Location Assignment: Flexible

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

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