Python Full Stack Developer

As a Software Engineer on our Platform Observability team, you will be at the heart of our engineering ecosystem. In this role, you will champion the adoption of modern telemetry standards, build robust data pipelines to handle metrics, logs, and traces daily, and create intuitive tooling that helps our engineering organization detect, diagnose, and resolve complex system issues before they impact our users. 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.

Skills RequiredGoogle Cloud Platform, Angular, Java, Python, Big Query, Big Data

Skills PreferredDesign and Build Data Pipelines: Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on Google Cloud Platform. Service-Oriented Architecture (SOA) and Microservices: Design and implement SOA and microservices-based architectures to ensure modular, flexible, and maintainable data solutions. 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 Google Cloud Platform 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 Google Cloud Platform's native row- and column-level security features. Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions. Work closely with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering. Automate data platform processes to enhance reliability, reduce manual intervention, and improve operational efficiency.

Experience RequiredMinimum 5 years of experience as a Software Engineer Proficient in Python with minimum 5 years of experience. Java experience will be a plus. Minimum 1-year experience with Angular, React or Vue Minimum 3-year experience with Google Cloud Platform, Azure or AWS Cloud platformsProficient in Java, angular or any javascript technology with experience in designing and deploying cloud-based data pipelines and microservices using Google Cloud Platform 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. 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 Google Cloud Platform technologies. 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. Must possess excellent SQL skills, including query optimization and data manipulation. Data Governance and Security: Understanding of data governance frameworks and implementing RBAC, encryption, and data masking in cloud environments. CI/CD and Automation: 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. o Ensure adherence to SDLC best practices, independently managing feature design, coding, testing, and production releases. Problem-Solving: Strong analytical skills with the ability to troubleshoot complex data platform and microservices issues. Certifications (Preferred): Google Cloud Platform Data Engineer, Google Cloud Platform Professional Cloud

Experience PreferredGoogle Cloud Platform experience preferred

Education RequiredBachelor's Degree

The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.