Full Stack Engineer

Full Stack Engineer

About the Role -

We are looking for a Full Stack Engineer to join our engineering team and work on a centralized Data Lakehouse and AI Intelligence Platform.

The role sits at the intersection of product engineering, data infrastructure, and automation, offering an opportunity to work across application, backend, data, and infrastructure layers. You will be responsible for building and enhancing scalable applications, backend services, data workflows, and platform capabilities while leveraging AI-assisted development tools to improve engineering efficiency.

Key Responsibilities -

• Develop and maintain full stack applications using Next.js and Python.
• Design, build, and maintain backend services, APIs, and microservices.
• Contribute to data infrastructure and lakehouse workflows.
• Build, maintain, and optimize ETL pipelines and workflow orchestration using tools such as Prefect and Hatchet.
• Work with infrastructure and data components including StarRocks and MinIO.
• Support containerized deployments, CI/CD pipelines, and environment management using Docker and Docker Swarm.
• Contribute to platform reliability, observability, monitoring, performance, and operational excellence.
• Use Git and collaborative development practices for day-to-day engineering and delivery.
• Leverage AI-assisted development tools to accelerate development, improve code quality, and enhance engineering workflows.
• Troubleshoot technical issues and contribute to improving system performance, scalability, and reliability.
• Take ownership of projects and work collaboratively across application, data, and infrastructure layers.

What We’re Looking For -

• 2–3 years of hands-on software development experience.
• Strong experience with Next.js and Python.
• Good understanding of full stack development, REST APIs, and API-driven architecture.
• Experience working with or supporting microservices.
• Practical knowledge of Docker, containerized deployments, and CI/CD.
• Proficiency with Git and collaborative software development practices.
• Exposure to data pipelines, orchestration, data infrastructure, or platform engineering.
• Ability to effectively use AI tools for software development and engineering productivity.
• Strong problem-solving and debugging skills.
• Ability to work independently, take ownership, and learn quickly.

Good to Have -

• Experience with data lakehouse or analytics infrastructure.
• Exposure to MPP databases, particularly StarRocks or similar technologies.
• Experience with Prefect, Hatchet, or other workflow orchestration frameworks.
• Familiarity with monitoring, logging, alerting, and DevOps automation.
• Experience building internal tools or AI-powered workflows.
• Understanding of system performance tuning, scalability, and reliability.