Python Full Stack Developer
Stefanini Group is hiring!
Stefanini is looking for a Python FullStack Developer (Dearborn, MI)
For quick apply, please reach out to Adil Khan at 248-728- 6424/ adil.khan@stefanini.com
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 Required
GCP, Angular, Java, Python, Big Query, Big Data
Skills Preferred-
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. -
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. -
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.