Associate Tech Lead – Engineering Commodity

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Where is the work:

Monday to Thursday, work onsite with your colleagues. Fridays, choose your work location, balancing what your work requires.

 

 

What will you do:

In this role you will:

• Gather and evaluate project data from several sources to develop viewpoints and recommendations.
• Develop and manage reporting tools and dashboards for monitoring project progress, milestones, and key performance metrics.
• Interact with project managers and stakeholders to identify data requirements and validity.
• Analyze project progress and accomplishments to identify patterns, dangers, and areas for improvement.
• Assist the PMO in creating and implementing project management policies and standards of excellence.
• Assist with project progress updates, management summaries, and presentations.
• Improve decision-making by providing independent evaluations and data-driven insights.
• Maintain data integrity and consistency throughout all project management tools and platforms.
• Participate in PMO meetings and contribute to the continuous improvement of PMO processes.

What you will bring:

Job Title: Associate Tech Lead – Engineering Commodity Classification

Job Summary

The Associate Tech Lead – Engineering Commodity Classification is responsible for supporting enhancement and maintenance component data by adopting technology solutions related to engineering commodity classification, with additional focus on Data Analytics, Artificial Intelligence, and strong design and product engineering domain knowledge. This role works closely with business stakeholders, product owners, architects, engineering teams, data teams, and development teams to deliver scalable, reliable, and efficient solutions that improve classification accuracy, product data quality, engineering decision-making, and business process effectiveness.

Key Responsibilities

• Support and maintenance of Engineering Commodity Classification in Team Center.
• Collaborate with business stakeholders, engineering teams, product owners, IT teams, analytics teams, and cross-functional partners to gather, analyze, and translate business requirements into effective technical solutions.
• Support the integration of Engineering Commodity Classification systems with enterprise applications, engineering platforms, data platforms, and reporting tools.
• Apply design engineering and product engineering background knowledge to better understand component structures, product configurations, engineering attributes, and classification logic.
• Work closely with product engineering and design teams to align commodity classification processes with engineering standards, product structures, BOM attributes, and design requirements.
• Contribute to Data Analytics initiatives by supporting data extraction, transformation, reporting, dashboard development, and insight generation.
• Assist in building and enhancing data models, data pipelines, and analytical solutions to support business and engineering decisions.
• Support Artificial Intelligence and automation use cases, including intelligent classification, predictive analysis, recommendation models, and process optimization where applicable.
• Identify opportunities to improve classification accuracy and workflow efficiency using engineering knowledge, analytics, and AI-driven approaches.
• Contribute to testing, deployment, release coordination, and post-production validation activities.
• Monitor application performance, system stability, data quality, and support production issue resolution.
• Maintain and update technical documentation, including workflows, design documents, support guides, data definitions, and change records.
• Drive continuous improvement in application functionality, analytics capability, AI adoption, and technical delivery practices.

Required Skills and Qualifications

• Bachelor’s degree in mechanical / electrical engineering, Product Engineering, Data Science, or a related field.
• Experience in team center systems support, analytics, and technical leadership roles.
• Knowledge of enterprise application integration, APIs,
• Understanding of Data Analytics concepts, reporting, dashboarding, and data interpretation.
• Exposure to Artificial Intelligence / Machine Learning concepts and their practical application in business or engineering processes.
• Strong design engineering or product engineering background knowledge, with understanding of engineering components, product structures, specifications, attributes related to HVAC Industry and classification concepts.
• Familiarity with engineering data, BOM structures, component taxonomy, and product-related business processes.
• Strong analytical, problem-solving, and troubleshooting skills.
• Ability to collaborate effectively with cross-functional business, technical, engineering, and data teams.
• Good verbal and written communication skills.

Preferred Qualifications

• Experience supporting engineering, classification, product data, supply chain, or commodity in PLM and ERP systems.
• Familiarity with databases, SQL, data pipelines, business intelligence tools, or reporting platforms.
• Ability to mentor junior team members to manage Part Classification and data developers or analysts and contribute to team capability building.
• 7-9yrs of working experience in product engineering, design engineering, component classification, or product lifecycle management processes.

Key Competencies

• Technical problem-solving
• Data-driven decision-making
• Engineering domain understanding
• Collaboration and teamwork
• Ownership and accountability
• Continuous improvement mindset
• Communication and stakeholder management
• Quality and delivery focus
• Innovation and analytical thinking

We offer competitive compensation and comprehensive benefits and programs. We are an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, pregnancy, age, marital status, disability, status as a protected veteran, or any legally protected status.