The Software Engineer leads full-stack development, manages cloud infrastructure, mentors developers, and ensures integration of ML models in manufacturing analytics.
This position is in Manufacturing analytics team within the Global Data Insight & Analytics (GDI&A) department. The Software Engineer is responsible for the design, development, testing, and maintenance of software applications that support manufacturing data and metrics. You will work across the entire software development lifecycle, including architecture design, coding, and deployment. The role requires full-stack capabilities to manage both user interfaces and server-side components.
Responsibilities- Technical Leadership: Serve as the "Tech Anchor" for the squad, making high-level design choices and dictates technical standards (coding standards, tools, and platforms) to ensure consistency and quality.
- Full-Stack Development: Lead the development of responsive, high-performance web applications using React/Angular, while building robust, scalable microservices in Python/Java.
- Cloud Infrastructure & Management: Architect and manage any cloud-native infrastructure (Google Cloud Platform is preferred) ensuring high availability, security, and cost-optimization for analytics workloads.
- DevOps & CI/CD Excellence: Design and maintain advanced CI/CD pipelines (Tekton/Jenkins, etc). Drive "Automate Everything" philosophies, including automated testing, deployment, and infrastructure-as-code (IaC).
- Manufacturing Analytics Support: Collaborate with Data Scientists and other Software Engineers to productionalize ML models and data pipelines, ensuring they are integrated into stable, user-facing software.
- Mentorship & Code Quality: Conduct rigorous code reviews and pair programming sessions. Mentor junior and mid-level engineers to elevate the overall technical competency of the team.
- System Architecture: Design complex system integrations, ensuring seamless data flow between shop-floor IoT devices, Data Platform and cloud-based analytics engines.
- Experience: 10+ years of professional software development experience in enterprise-grade environments.
- Backend Expertise: Expert-level proficiency in Python (FastAPI/Flask/Django) or Java (Spring Boot).
- Frontend Proficiency: Strong hands-on experience with either React or Angular frameworks for building complex, data-driven dashboards.
- CI/CD & DevOps: Proven track record of implementing and managing CI/CD pipelines, specifically with Tekton or similar Kubernetes-native tools.
- Cloud Mastery: Extensive experience with Google Cloud Platform (GCP), including GKE (Google Kubernetes Engine), Cloud Run, BigQuery, and IAM.
- Education: Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.
- Manufacturing Domain Knowledge: Experience working with industrial data, IIoT (Industrial Internet of Things), or manufacturing systems.
- Data Engineering Skills: Familiarity with data orchestration tools (e.g., Airflow) and streaming technologies (e.g., Kafka or Pub/Sub).
- Infrastructure as Code: Deep experience with Terraform or Pulumi for managing GCP resources.
- Advanced Leadership: Experience leading "Agile" transformations or acting as a lead architect for multi-year software projects.
- Certifications: GCP Professional Cloud Architect or Professional Data Engineer certifications.
Top Skills
Angular
BigQuery
Django
Fastapi
Flask
Gke
Google Cloud Platform
Java
Jenkins
Kafka
Pub/Sub
Python
React
Spring Boot
Tekton
Terraform
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