We are seeking an experienced Automotive Engineer – NPD CAD Designer & Analytics Specialist to join our Global Engineering team in Chennai, reporting to the CAD Manager LL6. This role is primarily focused on leading the delivery of high-quality CAD engineering for Interior Trims (IP, CNSL, Registers, Door Trims, Hard Trims & Soft Trims), supporting critical GPDS milestones (V0, V1, V2, FDJ) and ensuring FECDS compliance through Ford Process. You will own the entire Interiors NPD lifecycle — from A-surface evaluation and surface-to-CAD conversion, through DPA evaluation using Vis-Mockup, to releasing items in Teamcenter as part of the P-release process — while also preparing 2D drawings that meet Ford's global standards and timelines.
In addition to core CAD/NPD responsibilities, this role offers an opportunity to apply data analytics and foundational machine learning skills to engineering data, helping the team identify trends, forecast workloads, and improve decision-making using tools such as Python and SQL/BigQuery. This is not a primary data science role; rather, it is intended for a CAD/NPD engineer who brings complementary analytical capability to enhance engineering efficiency and insight generation. The ideal candidate is a proactive, detail-oriented professional with strong Ford-specific tool expertise, a solid grasp of vehicle architecture and assembly sequences, and the curiosity to leverage data-driven approaches where they add value — all while embodying One Ford Behavior in a global, collaborative environment.
CAD / NPD Engineering (Primary Focus)
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Deliver 3D CAD for Interior Trims (IP, CNSL, Registers, Door Trims, Hard Trims & Soft Trims) using Catia, 3DX, Teamcenter, and Vis-Mockup, along with 2D drawings and P-release process deliverables for global and region-specific programs.
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Manage CDHR/BOM processes using CDHR and FEDEBOM to ensure part claiming ownership, timely CAD population, and CDHR health tracking across all program gateways; resolve CDHR NOK issues in collaboration with Engineering & Suppliers.
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Perform DPA evaluations, including digital assembly checks, interface/alignment validation, distance measurements, and dynamic clearance studies using Vis-Mockup.
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Prepare and deliver precise 2D drawings in accordance with FECDS standards and Ford design rules.
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Collaborate cross-functionally with D&R Engineers to ensure all CAD deliverables meet Ford standards at every gateway/milestone.
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Ensure every gateway/milestone is aligned with Ford standards and design rule requirements.
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Drive innovation by participating in efficiency initiatives such as new Catia macros or CAD process automation.
Data Analytics & ML Support (Secondary Focus)
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Apply basic exploratory data analysis (EDA) and statistical techniques to engineering, BOM, and CDHR datasets to identify trends and anomalies relevant to NPD workload and complexity.
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Support the development of simple forecasting or predictive models (e.g., regression-based) to help estimate engineering workload and highlight complexity drivers.
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Write SQL queries (including in BigQuery) to extract and analyze engineering data as needed to support reporting and insight generation.
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Assist in building or maintaining lightweight dashboards to visualize engineering trends for team and stakeholder reviews.
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Collaborate with Analytics/Data Engineering teams when deeper AI/ML expertise is required, providing domain context and data interpretation support.
Education
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Bachelor's degree in Engineering (Mechanical/Automobile) or related discipline.
Experience
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8+ years of experience in Automotive Product Development.
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At least 4–6 years of specialized experience in new part development (CAD/NPD).
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Proven experience supporting CAD milestones (V0/V1/V2 & FDJ) within a Ford environment is highly preferred.
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Basic to intermediate hands-on experience (1+ years) applying data analysis or introductory machine learning techniques is a plus, but not a core requirement.
Functional/Technical Skills — CAD/NPD (Core)
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Advanced software proficiency in Catia V5, 3DX, Teamcenter, and Vis-Mockup.
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Expert knowledge of Teamcenter (AL-PL & P-Release process) and Ford BOM management systems (FEDE, CDHR).
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In-depth understanding of DPA process, vehicle architecture, systems/sub-systems, and assembly sequence logic.
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Knowledge of FMEAs and engineering quality standards.
Functional/Technical Skills — Data & Analytics (Supporting, Good to Have)
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Working knowledge of Python for data analysis (e.g., Pandas, NumPy) and basic familiarity with common ML libraries (e.g., Scikit-learn) is a plus.
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Basic SQL skills, ideally including exposure to Google BigQuery.
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General awareness of Google Cloud Platform (GCP) tools such as Vertex AI is a plus, but not required.
Preferred Skill Sets
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Strong interpersonal and communication skills to manage stakeholders, suppliers, and global customers.
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Highly motivated self-starter who can manage multiple tasks simultaneously under tight GPDS timelines.
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Ability to work across time zones and diverse cultures, always demonstrating "One Ford" behaviors.
