DLA - Senior Engineer (Full-stack, FastAPI, PLC)

General Motors; Bengaluru; Hybride; INR 1 200 000 - 1 800 000; Plein temps

Résumé du poste

General Motors in Bengaluru is seeking a Manufacturing Data Analytics Engineer to accelerate Mfg 4.0 initiatives. You will apply data analytics across GM manufacturing plants globally to solve complex problems with big data, building data pipelines, dashboards, and engineering applications.

Hybrid work model; travel limited but may include short international assignment for training. You will collaborate with controls, manufacturing, data science, cybersecurity, and IT to improve visibility,

Qualifications

• 5+ years of professional software engineering experience building and supporting production full-stack applications.
• 3+ years delivering manufacturing intelligence or data-intensive enterprise applications across frontend, backend, and data layers.
• Advanced TypeScript/JavaScript skills with React, including component architecture, state management, data visualization, responsive and accessible user interfaces, and frontend testing.
• Strong Python development skills with FastAPI or comparable frameworks, including asynchronous programming, REST/OpenAPI service design, request validation, dependency management, and automated testing.

Responsabilités

• Design, develop, and maintain full-stack manufacturing intelligence applications using modern frontend, backend, and database technologies.
• Build intuitive React/TypeScript user experiences for manufacturing dashboards, workflow tools, operational insights, and engineering applications.
• Develop scalable backend services and APIs using Python and FastAPI or comparable frameworks, with clear service boundaries, resilient error handling, and efficient request processing.
• Integrate applications with manufacturing and enterprise systems, including MES, SCADA, PLC/controls data, historians, equipment interfaces, and event-driven data services.
• Design and optimize PostgreSQL data models, queries, and data pipelines for production, quality, equipment, and process information.
• Implement secure authentication, authorization, auditability, and data-access controls for applications used across GM manufacturing and engineering environments.
• Deploy and operate applications across enterprise, cloud, and edge environments using Docker, Kubernetes, CI/CD automation, and production monitoring.
• Create automated unit, integration, and end-to-end tests and establish engineering practices that improve application reliability, maintainability, and release quality.
• Translate manufacturing and engineering problems into clear technical designs, user stories, acceptance criteria, and measurable product outcomes.
• Collaborate with controls, manufacturing, quality, data science, cybersecurity, and IT teams to deliver solutions that improve visibility, productivity, quality, and decision-making.
• Troubleshoot production issues, perform root-cause analysis, and implement performance and reliability improvements across the application stack.
• Document architecture, APIs, deployment procedures, operating standards, and support processes while contributing to a culture of continuous improvement.

Connaissances

React/TypeScript

Python/FastAPI

PostgreSQL

SQL/Data modeling

Docker

Kubernetes

CI/CD

Data pipelines

REST/OpenAPI

Git

Formation

Bachelor's degree in CS/ENG

Outils

Docker

Kubernetes

Git

FastAPI

Description du poste

Job Description Sponsorship : GM DOES NOT PROVIDE IMMIGRATION-RELATED SPONSORSHIP FOR THIS ROLE. DO NOT APPLY FOR THIS ROLE IF YOU WILL NEED GM IMMIGRATION SPONSORSHIP (e.g., H-1B, TN, STEM OPT, etc.) NOW OR IN THE FUTURE.

Work Arrangement: This role is categorized as hybrid. This means the successful candidate is expected to report to the office four times per week or other frequency dictated by the business.

The Role

Global Manufacturing Engineering at GMTCI is a bridge between Global Manufacturing Plants & Global Product Engineering in getting the Product & Process Right. GMTCI's strategy is to "Execute Design / Simulation / Virtual / Engineering Workshare for the Globe + Enable Factory for the Future"

This position of Manufacturing Data Analytics Engineer is a Mfg 4.0 initiative in ME Vehicle Systems Automation Group which is primarily responsible for applying Data Analytics techniques on GM manufacturing processes in GM manufacturing plants across the globe to solve complex manufacturing business problems with big data. In this position, the engineer supports critical business operations and decision making through creation domain data exploration, data processing pipeline, and business intelligence reports.

This is primarily a non-travel job. Business travel will be necessary on special requirements and will be for a short duration. Depending on the need, there will be an International Short-Term assignment for 6 months in the first year for training & development.

What You'll Do

• Design, develop, and maintain full-stack manufacturing intelligence applications using modern frontend, backend, and database technologies
• Build intuitive React/TypeScript user experiences for manufacturing dashboards, workflow tools, operational insights, and engineering applications
• Develop scalable backend services and APIs using Python and FastAPI or comparable frameworks, with clear service boundaries, resilient error handling, and efficient request processing
• Integrate applications with manufacturing and enterprise systems, including MES, SCADA, PLC/controls data, historians, equipment interfaces, and event-driven data services
• Design and optimize PostgreSQL data models, queries, and data pipelines for production, quality, equipment, and process information
• Implement secure authentication, authorization, auditability, and data‑access controls for applications used across GM manufacturing and engineering environments
• Deploy and operate applications across enterprise, cloud, and edge environments using Docker, Kubernetes, CI/CD automation, and production monitoring
• Create automated unit, integration, and end‑to‑end tests and establish engineering practices that improve application reliability, maintainability, and release quality
• Translate manufacturing and engineering problems into clear technical designs, user stories, acceptance criteria, and measurable product outcomes
• Collaborate with controls, manufacturing, quality, data science, cybersecurity, and IT teams to deliver solutions that improve visibility, productivity, quality, and decision‑making
• Troubleshoot production issues, perform root‑cause analysis, and implement performance and reliability improvements across the application stack
• Document architecture, APIs, deployment procedures, operating standards, and support processes while contributing to a culture of continuous improvement.

Your Skills & Abilities (Required Qualifications)

• Bachelor's or higher degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or equivalent experience
• Ability to work effectively in both central engineering and plant environments, including time on the plant floor around operating equipment
• 5+ years of professional software engineering experience building and supporting production full‑stack applications
• 3+ years of experience delivering manufacturing intelligence, industrial software, or data‑intensive enterprise applications across frontend, backend, and data layers
• Advanced TypeScript/JavaScript skills with React, including component architecture, state management, data visualization, responsive and accessible user interfaces, and frontend testing
• Strong Python development skills with FastAPI or comparable frameworks, including asynchronous programming, REST/OpenAPI service design, request validation, dependency management, and automated testing
• Advanced SQL and PostgreSQL skills, including relational data modeling, schema design, migrations, indexing, query and transaction performance, and data‑quality controls
• Experience delivering manufacturing intelligence, industrial software, or data‑intensive enterprise applications that connect operational data to business and engineering workflows
• Experience designing data pipelines and event‑driven architectures for equipment telemetry, time‑series data, production data, quality data, and manufacturing workflows
• Hands‑on experience with Git, Docker, Kubernetes, CI/CD automation, environm