POSITION DESCRIPTION:

We are looking for a Full Stack Developer supporting enterprise data lake for all global embedded modem, Smart Mobility experiments, Manufacturing and other enterprise data. The engineer will ensure that the platform delivers capabilities for ingesting, classifying, cataloguing, quality, data governance, and data availability in the data lake. Join us and challenge your Software Engineering expertise and analytical skills to help create a smart future. A platform software Engineer is a versatile developer with expertise in Java or Python and a strong foundation in cloud platforms to build and manage applications at scale. Generally, platform engineers fall into two categories: backend engineers, who design and implement microservices with robust APIs, and full-stack engineers, who deliver native UI/UX solutions, and ability to develop frameworks and services to enable an enterprise data platform. With a solid understanding of the SDLC and hands-on experience in Git and CI/CD, platform engineers can independently design, code, test, and release features to production efficiently.

EXPERIENCE REQUIRED

• Minimum 5 years of experience as a Software Engineer
• 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 to deliver platform features, and design & orchestrate platform services to deliver data platform capabilities.
• 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.
• Knowledge of front-end and back-end technologies, enabling collaboration on data access and visualization layers (e.g., React, Node.js). o 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.
• Experience with relational (e.g., PostgreSQL, MySQL) and NoSQL databases, as well as columnar databases like BigQuery.
• Understanding of data governance frameworks and implementing RBAC, encryption, and data masking in cloud environments.
• Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform, and automation frameworks.
• Manage code changes with GitHub and troubleshoot and resolve application defects efficiently.
• Ensure adherence to SDLC best practices, independently managing feature design, coding, testing, and production releases.
• Strong analytical skills with the ability to troubleshoot complex data platform and microservices issues.
• Certifications (Preferred): GCP Data Engineer, GCP Professional Cloud

EDUCATION REQUIRED:

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field.
• Master’s degree or equivalent experience preferred

*LISTED SALARY RANGES MAY VARY BASED ON EXPERIENCE, QUALIFICATIONS, AND LOCAL MARKET. ALSO, SOME POSITIONS MAY INCLUDE BONUSES OR OTHER INCENTIVES**

Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We also speak with you about the process, including interviews and job offers.

• Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on GCP.
• 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.
• Lead the ingestion and integration of data from various sources into the data platform, ensuring data is standardized and optimized for analytics.
• Utilize GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that meet business needs.
• Implement and manage data governance, access controls, and security best practices while leveraging GCP’s native row- and column-level security features.