OEX Intelligence Engineer

Clarios; Celaya; Presencial; MXN 670.000 - 1.004.000; Jornada completa

Descripción de la vacante

Clarios is seeking an OEX Intelligence Engineer to drive data-driven decisions across the Celaya plant. You will leverage analytics, dashboards, and digital solutions to improve OEE and GCC performance and support continuous improvement initiatives.

You will lead data projects, collaborate with Production, Quality, Engineering, and Operations, and coach others in analytics and data storytelling while ensuring data integrity and governance.

Formación

• Bachelor's degree in a related field.
• Experience in Data Analytics or BI roles.
• Experience delivering analytics solutions that improve performance.

Responsabilidades

• Execute analytics projects to improve OEE and GCC performance.
• Develop dashboards and visualization tools for operational decisions.
• Generate insights from manufacturing data (descriptive to real-time).
• Lead workshops and cross-functional problem solving using data-driven methods.
• Support digitalization roadmap through analytics and data integration.
• Collaborate with cross-functional teams to solve business challenges.
• Train employees on data visualization and analytics tools.

Conocimientos

Analytical thinking

Large data handling

storytelling & communication

Influence stakeholders

Manufacturing domain experience

Machine learning concepts

Data visualization

Educación

Bachelor's degree in Data Science/Math/Stats/CS/Industrial Eng.

Herramientas

SQL

Hadoop

Spark

Python/Scala

Descripción del empleo

Position Summary

The OEX Intelligence Engineer is responsible for driving data-driven decision-making across the plant by leveraging advanced analytics, visualization tools, and digital solutions. This role identifies opportunities to improve OEE and GCC performance, supports Operational Excellence initiatives, and promotes a culture of continuous improvement through actionable insights and data enablement.

What You Will Do

• Execute advanced analytics projects focused on improving OEE and GCC performance.
• Develop dashboards, reports, and visualization tools to support operational and strategic decisions.
• Generate descriptive, diagnostic, predictive, and real-time insights from manufacturing data.
• Analyze large data sets to identify trends, correlations, patterns, and improvement opportunities.
• Lead workshops and cross-functional problem-solving activities using data-driven methodologies.
• Support the plant digitalization roadmap through analytics and data integration initiatives.
• Collaborate with Production, Quality, Engineering, and Operations teams to solve business challenges.
• Train and coach employees on data visualization tools, analytics, and effective use of data.
• Support Daily Management System (DMS) processes through reporting, analytics, and data storytelling.
• Promote Operational Excellence tools and continuous improvement initiatives throughout the plant.
• Ensure data integrity, security, and governance standards are maintained.
• Provide analytical support and recommendations to plant leadership.

What Will Help You Succeed

• Strong analytical and problem-solving capabilities.
• Experience working with large and complex data sets.
• Knowledge of SQL, Hadoop, Spark, and database management.
• Proficiency in Python, Scala, or similar programming languages.
• Experience with Business Intelligence and data visualization tools.
• Knowledge of Machine Learning and Big Data technologies.
• Ability to transform data into actionable business insights.
• Effective communication and storytelling skills.
• Ability to influence stakeholders and drive a data-driven culture.
• Experience in manufacturing, continuous improvement, or Operational Excellence environments.
• Strong collaboration skills and ability to work with cross-functional teams.

Key Competencies

• Analytical Thinking
• Problem Solving
• Continuous Improvement
• Results Orientation
• Communication
• Collaboration
• Leadership
• Innovation
• Customer Focus
• Attention to Detail
• Adaptability
• Time Management
• Coaching and Mentoring

Education

Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, Industrial Engineering, Applied Mathematics, or a related field.

Experience

• Previous experience in Data Analytics, Data Science, Business Intelligence, or related analytical roles.
• Experience developing analytics solutions that support operational or business performance improvements.

Language

• Advanced English proficiency.

About Clarios

Clarios is the global leader in advanced, low-voltage battery technologies for mobility. Our batteries and smart solutions power nearly every type of vehicle and are found in 1 of 3 cars on the road today. With around 18,000 employees in over 100 countries, we bring deep expertise to our Aftermarket and OEM partners, and reliability, safety and comfort to everyday lives. We answer to the planet with a rigorous sustainability focus – advancing best-in-class sustainability practices and advocating for them across our industry. We work to ensure 100% of our products sold are recyclable, and we recycle 8,000 batteries an hour in our network. You can find more information here (PDF).

To All Recruitment Agencies

Clarios does not accept unsolicited agency resumes/CVs. Please do not forward resumes/CVs to our careers email addresses, Clarios employees or any other company location. Clarios is not responsible for any fees related to unsolicited resumes/CVs.

Equal Employment Opportunity

Clarios, LLC is an equal employment opportunity and affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, protected veteran status, status as a qualified individual with a disability, or any other characteristic protected by law. For more information, please view EEO is the Law, EEO is the Law (supplement), and Pay Transparency Non-discrimination. If you are an individual with a disability and you require an accommodation during the application process, please email [e-mail].