Staff Manufacturing Engineer

ZT Systems•Secaucus, NJ

About The Position

The Staff Manufacturing Engineer leads the development, applied research, and implementation of industrial models, business analytics solutions, and analytical tools to set manufacturing performance targets and support business decision-making. The role works with manufacturing leadership and cross-functional teams to analyze operational challenges and evaluate improvement opportunities, helping define changes to resources, infrastructure, and manufacturing processes based on insights from the organization’s analytical tools. The position leads the Industrial and BI Engineering team in turning data into insights and business decisions. It owns and enhances business intelligence models and decision-support tools for short-term and long-range planning, and provides technical leadership to junior team members. The role applies statistical analysis, analytical modeling, optimization, simulation, and data mining to manufacturing processes and operational challenges, and leads cross-functional projects from problem definition through implementation. The engineer collaborates with Manufacturing, Supply Chain, Operations, Engineering, Finance, and other departments. The role uses SQL, Python, and business intelligence tools to analyze and visualize complex data, and communicates findings as clear, actionable recommendations for operational performance, resource planning, technology investments, and process improvement.

Requirements

Bachelor’s degree in Industrial Engineering, Mechanical Engineering, or a related field, with 2 years of experience; alternatively, a Master’s or Doctoral degree with any amount of experience.
Relevant experience in an engineering role.
Experience in manufacturing environments.
Experience with business intelligence and analysis tools such as SQL, Python, Tableau, and Power BI.
Experience with Microsoft Office tools, including Outlook, Excel, and Word.
Fluency in mathematical computing with at least one programming language, such as Python, R, or Java, and ability to learn technical methods and tools independently.
Fluency in data visualization and presentation, including simplifying results and statistical concepts into actionable insights.
Hands-on experience building, running, and analyzing simulations; designing analytical models; and applying statistical analysis and optimization techniques.
Ability to explain complex, often data-driven topics through clear overviews and insights.
Experience applying analytical methods, statistical analysis, and data-driven decision-making to improve manufacturing performance and business outcomes.
Experience working with cross-functional teams to solve complex operational and business challenges using data analytics.
Strong analytical and problem-solving capabilities, communication skills, initiative, and ability to thrive in a fast-paced environment.
Growth mindset and commitment to continuous learning; ability to take independent initiative and complete projects with urgency.

Nice To Haves

Exposure to business, finance, or economics.

Responsibilities

Lead the Industrial and BI Engineering team in transforming data into insights and business decisions that guide the manufacturing organization.
Develop, maintain, and continuously improve industrial models, analytical tools, data structures, and business intelligence solutions for operational and strategic decision-making.
Investigate and propose new technologies and data-driven solutions in automation, modern manufacturing, business intelligence, and advanced analytics.
Identify and lead enterprise-level Kaizen and continuous improvement projects using statistical analysis, optimization, and structured problem-solving to improve cycle time, cost, capacity utilization, throughput, and on-time delivery.
Serve as the focal point for engineering analysis related to changes in technology, AI, products, manufacturing processes, and systems; provide evidence-based recommendations.
Own and enhance business intelligence models and decision-support tools for short-term and long-range planning, ensuring accuracy, continuous improvement, and actionable insights.
Conduct statistical and business analyses across departments using SQL, Python, and business intelligence tools to access, analyze, manipulate, and visualize complex multivariate data.
Lead cross-functional analytical projects from problem definition through solution implementation, identifying business needs, developing analytical strategies, and communicating recommendations to stakeholders.
Provide technical leadership and guidance to junior team members on complex analytics, modeling, and continuous improvement projects; promote analytical best practices and data-driven decision-making.
Apply advanced statistical, analytical, optimization, and simulation methodologies to manufacturing processes and operational challenges.
Conduct applied research and analytical evaluations of manufacturing processes, production metrics, and business challenges to identify trends and improvement opportunities.
Develop, validate, and improve predictive and prescriptive models, dashboards, and decision-support solutions for capacity planning, resource optimization, cost analysis, forecasting, and manufacturing performance.
Collaborate with Manufacturing, Supply Chain, Operations, Engineering, and Finance to translate analytical findings into recommendations for resource planning, technology investments, process improvements, and operational decisions.
Evaluate emerging analytical methodologies, statistical techniques, optimization approaches, and business intelligence technologies for manufacturing innovation and continuous improvement.