Moog
EHSDataManager
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“EHS Data Manager at Moog. Skills: Data management, Data reporting, Data analytics, EHS data. Lead and develop the EHS data team. Define the vision and roadmap for EHS data”
What You'll Achieve.
Support EHS reporting and analytics needs; Support compliance and risk management; Ensure reliable and timely data availability; Improve processes; Enable efficient data storage, transformation, and access; Ensure stability of the platform; Reduce manual effort; Improve data reliability; Enable advanced analytics; Proactively manage risk; Continuously improve EHS performance
Industry & Context.
Analytical skills; Problem-solving skills; Data-driven decision making
Access to U. S. export-controlled information
What They're Looking For.
Must Have
Bachelor's degree in data science, statistics, environmental science, or related field, Demonstrated experience leading data analytics processes and/or people, Foundational knowledge of data analysis concepts and techniques, At least five (5) years of experience with SQL, At least five (5) years of experience with Python, At least five (5) years of experience with ETL processing, At least five (5) years of experience with data warehousing, datalake and lakehouse concepts, At least five (5) years of experience with data modeling concepts, Ability to communicate insights to non-technical stakeholders, Ability to present information to all levels of the organization, Must live local to Buffalo
Nice to Have
Experience in Microsoft Azure Databricks highly desired, Experience in Microsoft Power BI, Azure Data Factory, a plus, Familiarity with EHS data a plus
What You'll Do.
Lead and develop the EHS data team
Define the vision and roadmap for EHS data
Serve as the primary point of contact for
Establish and maintain data standards
Oversee the development and maintenance of corporate dashboards
Oversee the maintenance of recurring EHS reports
Identify trends and opportunities for improvement
Translate data findings into meaningful insights
Provide recommendations for leadership
and system administrators
Maintain and enhance the EHS data ecosystem
Support EHS initiatives through targeted analytics
Provide predictive insights
Ensure alignment with regulatory and corporate reporting requirements
Align reporting cadence
and metric definitions
How You'll Work.
Team & Collaboration
Cross-functional teams; IT teams; Data engineering teams; Corporate EHS team; Business groups
Communication Scope
Present information; Communicate insights
Process & Methodology
Roadmap development
Full Job Description
Moog is a performance culture that empowers people to achieve great things. Our people enjoy solving interesting technical challenges in a culture where everyone trusts each other to do the right thing. For you, working with us can mean deeper job satisfaction, better rewards, and a great quality of life inside and outside of work. **Job Title** : EHS Data Manager **Reporting To:** Management, Business Program Management **Work Schedule:** Hybrid – Buffalo, NY Moog’s Corporate Group is hiring an **Environmental Health & Safety (EHS) Data Manager** to lead our EHS data strategy, strengthen global reporting and guide data-driven decision making across the company. In this role, you will have opportunities to design, build, and maintain scalable data pipelines and data models to support EHS reporting and analytics needs. You will also collect, analyze, and create outputs for Environmental Health & Safety data to support compliance and risk management by integrating data from multiple sources into centralized data platforms, ensuring reliable and timely data availability. You will establish data quality checks with key stakeholders, validation processes, and governance standards to ensure accuracy, consistency, and integrity of EHS data across systems. You will develop dashboards and reports for the Corporate EHS team to monitor performance metrics, collaborate with team members to ensure data accuracy, and provide data-driven recommendations to improve processes. It will be important for you to partner with IT and data engineering teams to optimize data architecture, support cloud-based data solutions (e.g., Azure, Databricks), and enable efficient data storage, transformation, and access to ensure the stability of the platform. You will also support the automation of dashboards and enhance system interoperability to reduce manual effort and improve data reliability. Through these efforts, you will enable advanced analytics, trend identification, and predictive insight
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