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Job Purpose and Impact

The Director, Data Engineering – Manufacturing Data job leads the team responsible for the execution of the tactical and strategic plans related to design, development and maintenance of robust data systems. This job provides guidance to the team that ensures the efficient processing and availability of data for analysis and reporting.

Key Accountabilities

• DATA SYSTEMS: Establishes and maintains robust data systems that support large and complex data products, ensuring reliability and accessibility for partners.
• SOLUTIONS DEVELOPMENT: Leads the development of technical products and solutions using big data and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust. .
• DATA PIPELINES: Oversees and guides the design and development of data pipelines that facilitate the movement of data from various sources to internal databases.
• DATA INFRASTRUCTURE: Handles the construction and optimization of data infrastructure, resolving appropriate data formats to ensure data readiness for analysis.
• DATA FORMATS: Examines and settles appropriate data formats to optimize data usability and accessibility across the organization.
• STAKEHOLDER MANAGEMENT: Liaises with partners to understand data needs and ensure alignment with organizational objectives.
• DATA FRAMEWORKS: Champions development standards and brings forward prototypes to test new data framework concepts and architecture patterns supporting efficient data processing and analysis and promoting standard methodologies in data management.
• AUTOMATED REPORTING SYSTEMS: Leads the creation and maintenance of automated reporting systems that provide timely insights and facilitate data driven decision making.
• DATA MODELING: Oversees data modeling to ensure the preparation of data in databases for use in various analytics tools and to configurate and develop data pipelines to move and improve data assets.
• TEAM MANAGEMENT: Manages team members to achieve the organization's goals, by ensuring productivity, communicating performance expectations, creating goal alignment, giving and seeking feedback, providing coaching, measuring progress and holding people accountable, supporting employee development, recognizing achievement and lessons learned, and developing enabling conditions for talent to thrive in an inclusive team culture.

Qualifications

• Minimum requirement of 6 years of relevant work experience. Typically reflects 10 years or more of relevant experience.

Preferred qualiications:

• Manufacturing, supply chain, industrial IoT, or operational technology experience.
• Experience enabling AI, machine learning, and advanced analytics through modern data platforms.
• Experience working with large-scale enterprise data ecosystems.
• Experience building product-oriented engineering organizations.
• Experience integrating ERP, manufacturing, historian, quality, maintenance, and operational data domains into common data models.
• Experience developing data capabilities that directly support decision intelligence and AI-driven operations.
• Leadership experience building and managing high-performing data engineering teams.
• Experience partnering with business leaders to translate operational needs into scalable technical solutions.
• Experience driving technology transformation and organizational change.