Fullstack Data Engineer (ID 1310)
Posted
Summary
Full-stack data engineer on an enterprise BI and data platform: designs data ingestion/ETL pipelines, builds backend REST APIs, and integrates frontend dashboards. Core stack includes SQL, Python (and/or Java/Node.js), Docker, AWS, Terraform, and BI tools such as Superset.
Role Summary
We are looking for a strong Full Stack Data Engineer to contribute to the design and development of
scalable enterprise BI and data platform capabilities.
The role requires hands-on experience across data engineering, backend services, APIs, and frontend
integration to support modern analytics and platform initiatives.
The engineer will work closely with platform leads, architects, frontend engineers, and business
stakeholders to build reusable data and reporting solutions that support enterprise-scale analytics and
operational visibility.
Key Responsibilities
• Design and develop scalable data ingestion and transformation pipelines
• Build backend APIs and services supporting BI and analytics platforms
• Develop and integrate frontend components for dashboards and reporting interfaces
• Create reusable data models, reporting datasets, and platform services
• Collaborate with architects and engineering teams on scalable platform design
• Participate in CI/CD, code reviews, testing, and engineering standards adoption
• Support cloud-native and containerized platform initiatives
• Contribute to observability, monitoring, and operational improvements
Requirements
• Strong SQL and data modeling skills
• Python-based data processing and scripting
• ETL/ELT pipeline development
• Understanding of data transformation and integration concepts
• REST API and backend service development
• Experience with Python / Java / Node.js (one or more)
• Database integration and optimization
• Basic knowledge of React / Angular / JavaScript
• Exposure to dashboard and UI integration
• API consumption and frontend connectivity experience
• Understanding of CI/CD concepts
• Knowledge of Docker and containerization basics
• Exposure to AWS and cloud platform concepts preferred
• Experience with BI and reporting platforms
• Knowledge of Superset or analytics visualization tools
• Understanding of distributed systems and scalable architectures
• Exposure to Terraform / Infrastructure as Code (IaC)
• Awareness of observability and monitoring concepts