Ford Recruitment 2025 For Software Engineer

• Design and Build Data Pipelines: Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on GCP.
• Service-Oriented Architecture (SOA) and Microservices: Design and implement SOA and microservices-based architectures to ensure modular, flexible, and maintainable data solutions.
• Full-Stack Integration: Leverage your full-stack expertise to contribute to the seamless integration of front-end and back-end components, ensuring robust data access and UI-driven data exploration.
• Data Ingestion and Integration: Lead the ingestion and integration of data from various sources into the data platform, ensuring data is standardized and optimized for analytics.
• GCP Data Solutions: Utilize GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that meet business needs.
• Data Governance and Security: Implement and manage data governance, access controls, and security best practices while leveraging GCP’s native row- and column-level security features.
• Performance Optimization: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions.
• Collaboration and Best Practices: Work closely with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering.

Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field. Master’s degree or equivalent experience preferred.
• Technical Skills: Proficient in Java, angular or any javascript technology with experience in designing and deploying cloud-based data pipelines and microservices using GCP tools like BigQuery, Dataflow, and Dataproc.
• Ability to leverage best in-class data platform technologies (Apache Beam, Kafka, …) to deliver platform features, and design & orchestrate platform services to deliver data platform capabilities.
• Service-Oriented Architecture and Microservices: Strong understanding of SOA, microservices, and their application within a cloud data platform context. Develop robust, scalable services using Java Spring Boot, Python, Angular, and GCP technologies.
• Full-Stack Development: Knowledge of front-end and back-end technologies, enabling collaboration on data access and visualization layers (e.g., React, Node.js).
• Design and develop RESTful APIs for seamless integration across platform services.
• Implement robust unit and functional tests to maintain high standards of test coverage and quality.
• Database Management: Experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases, as well as columnar databases like BigQuery.