Senior Full Stack Software Engineer

As a candidate for the position, you should have a strong understanding of Service-Oriented Architecture (SOA) and Microservices, particularly in the context of a cloud data platform. Your knowledge of full-stack development, encompassing front-end and back-end technologies such as Angular, React, and Node.js, will be crucial for collaborating on data access and visualization layers. In addition, experience with both relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases, as well as columnar databases like BigQuery, is required for effective database management. You will be responsible for understanding data governance frameworks and implementing Role-Based Access Control (RBAC), encryption, and data masking in cloud environments to ensure data security. Familiarity with CI/CD pipelines, Infrastructure as Code (IaC) tools like Terraform, and automation frameworks will be essential for streamlining processes. Strong analytical skills are necessary for troubleshooting complex data platform and microservices issues. Your qualifications should include a B.Tech or M.Tech degree to qualify for this role. As part of your key job responsibilities, you will be tasked with designing and building scalable data pipelines and microservices on Google Cloud Platform (GCP) to support real-time and batch processing. Designing and implementing SOA and microservices-based architectures, ensuring modular, flexible, and maintainable data solutions, will be a core focus of your role. Utilizing your full-stack expertise, you will contribute to the seamless integration of front-end and back-end components, enabling robust data access and UI-driven data exploration. Leading data ingestion and integration efforts from various sources into the data platform, standardizing and optimizing data for analytics, will also be part of your responsibilities. Leveraging GCP services like BigQuery, Dataflow, Pub/Sub, Cloud Functions, among others, you will build and manage data platforms aligned with business needs. Implementing and managing data governance, access controls, and security best practices while utilizing GCP's native security features will be crucial. Continuous monitoring and improvement of performance, scalability, and efficiency of data pipelines and storage solutions will be required. Collaboration with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering is essential. Lastly, automating data platform processes to enhance reliability, reduce manual intervention, and improve operational efficiency will be a key focus area in this role.,