Manufacturing Analytics Lead

ZT Systems; Secaucus (NJ); On-site; USD 93,000 - 136,000; Full time

Benefits offered by this job

Bonus

401(k) retirement savings plan

Tuition reimbursement

Wellbeing resources

Job summary

ZT Systems, a Sanmina Company, seeks a Staff Manufacturing Engineer in Secaucus, NJ to lead analytics and BI initiatives shaping manufacturing performance. You will guide cross-functional teams, develop predictive models, and implement data-driven improvements across processes to boost efficiency and on-time delivery.

The role requires strong statistical and programming skills, BI tooling expertise (SQL, Python, Tableau, Power BI), and collaboration with Manufacturing, Supply Chain, and Finance.

Qualifications

• Bachelors in industrial/mechanical engineering or related field.
• Master/PhD acceptable with relevant experience.
• 2 years of engineering experience in manufacturing environment is required.
• Experience with BI tools (SQL, Python, Tableau, Power BI).
• Proficiency with MS Office tools and data visualization.

Responsibilities

• Lead Industrial and BI Engineering to turn data into insights for decision-making.
• Develop and maintain industrial models, analytics tools, and data structures.
• Identify opportunities for automation, analytics, and continuous improvement.
• Conduct statistical analysis and optimization to improve cycle time, cost, capacity, and delivery.
• Collaborate with cross-functional teams to translate findings into actions.

Skills

SQL

Python

Tableau

Power BI

Excel

Analytical thinking

Education

Bachelor’s degree in Industrial or Mechanical Engineering

Master’s or Doctoral degree

Tools

Tableau

Power BI

SQL

Python

Job description

ZT Systems, a Sanmina Company, seeks a Staff Manufacturing Engineer in Secaucus, NJ to lead analytics and BI initiatives shaping manufacturing performance. You will guide cross-functional teams, develop predictive models, and implement data-driven improvements across processes to boost efficiency and on-time delivery.

The role requires strong statistical and programming skills, BI tooling expertise (SQL, Python, Tableau, Power BI), and collaboration with Manufacturing, Supply Chain, and Finance.