Stanley Black & Decker, Inc. is a leading tool company seeking a Senior Manager, Data Engineering. In this role, you will lead a team of data engineers, develop scalable data architectures, and ensure data governance while collaborating with various teams to align data solutions with business objectives.
Responsibilities:
- Lead, mentor, and develop a team of data engineers, fostering a culture of innovation, accountability, and continuous improvement
- Execute the data engineering strategy in alignment with manufacturing and supply chain objectives
- Design and implement scalable, secure, and resilient data architectures across cloud (Azure, AWS) and hybrid environments
- Manage data acquisition and ingestion processes, including integration with PLCs, historians, SCADA, IoT, and manufacturing systems
- Support and enforce data governance, standards, and best practices for data quality, lifecycle management, and compliance
- Collaborate with IT, operations, quality, and supply chain teams to translate business requirements into actionable data solutions
- Develop and maintain real-time and batch data pipelines using technologies such as Snowflake, PowerBI, Power Automate, MQTT, Inductive Automation, Tulip, and SAP
- Provide insights into manufacturing KPIs and other critical metrics, ensuring data is contextualized and accessible for stakeholders
- Drive continuous improvement in data engineering processes, tools, and team capabilities
- Promote an action-oriented, inclusive, and collaborative team culture
- Ensure solutions comply with organizational standards and strategic direction
- Facilitate the sharing of ideas and best practices across the team using existing and emerging technologies
- Provide regular updates and ongoing support to management and key stakeholders
- Uphold high standards of work quality and contribute to the success of the team
Requirements:
- Bachelor's degree from an accredited institution in Computer Science, Data Engineering, Information Systems, Industrial Engineering, or a related field
- Minimum 7 years of professional experience in data engineering
- At least 2 years in a leadership role managing data engineering teams
- Experience with shop floor data sources (PLCs, historians, SCADA, IoT)
- Experience with cloud data platforms (Snowflake, Azure, AWS), data integration, and visualization tools (PowerBI)
- Knowledge of data governance, data architecture, and best practices for data quality and security
- Experience in the manufacturing industry