Design and Build Data Pipelines: Architect, develop, and maintain scalable data pipelines and microservices that support real-time and batch processing on GCP. Performance Optimization: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions. Established and active employee resource groups 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. 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. 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): GCP Data Engineer, GCP Professional Cloud
