Full Stack Engineer

The key responsibilities revolve around designing, building, and maintaining scalable data pipelines and microservices. This includes everything from data ingestion and integration from various sources to ensuring data governance, security, and performance optimization within a GCP environment (using services like BigQuery, Dataflow, Pub/Sub, and Cloud Functions). The role requires full-stack skills for seamless front-end and back-end integration and collaboration with various teams to establish best practices and automation. In short, the ideal candidate will be a highly skilled GCP data engineer capable of building and maintaining a robust and efficient data platform.

• 2 - 7 years of experience in data engineering or software engineering, with at least 1 - 2 years focused on cloud data platforms (GCP preferred).
• Technical Skills: Proficient in Java, SpringBoot & Angular/React with experience in designing and deploying cloud-based data pipelines and microservices using GCP tools like BigQuery, Dataflow, and Dataproc.
• Service-Oriented Architecture and Microservices: Strong understanding of SOA, microservices, and their application within a cloud data platform context.
• Full-Stack Development: Knowledge of front-end and back-end technologies, enabling collaboration on data access and visualization layers (e. g. Angular, React, Node. js).
• 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.
• Problem-Solving: Strong analytical skills with the ability to troubleshoot complex data platform and microservices issues.

Positions Location : Chennai / Bengaluru (Hybrid)

• 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.
• Full-Stack Integration: 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.
• Data Ingestion and Integration: Lead the ingestion and integration of data from various sources into the data platform, ensuring data is standardized and optimized for analytics.
• GCP Data Solutions: Utilize GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc. ) to build and manage data platforms that meet business needs.
• Data Governance and Security: Implement and manage data governance, access controls, and security best practices while leveraging GCP s native row- and column-level security features.
• Performance Optimization: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions.
• Collaboration and Best Practices: Work closely with data architects, software engineers, and cross-functional teams to define best practices, design patterns, and frameworks for cloud data engineering.
• Automation and Reliability: Automate data platform processes to enhance reliability, reduce manual intervention, and improve operational efficiency.