Full Stack Data Engineer

Key Responsibilities: 

• Architect & Develop: Design high-performance, scalable backend services using the Python stack and have a good understanding of Java 17+ and Spring Boot for migration projects.
• Data Integration: Build and maintain complex data pipelines and integration layers connecting our services to Databricks.
• Security First: Implement rigorous authentication and authorization patterns using OAuth2, OIDC in Python.
• AI Tooling: Develop backend frameworks that enable Agentic AI—creating tools, APIs, and "skills" that LLM-based agents can autonomously invoke.
• Data Persistence: Optimize database interactions and schema designs using Python packages, and can understand existing flows of Spring Data JPA/Hibernate.
• Hybrid Engineering: Use Python as the primary language and support, convert legacy Java code into Python.

Required Qualifications

• Experience: 3 to 5 years of professional experience in backend development.
• Python Stacks: Good hands-on experience with Python Stack for building backends, APIs, or ingestion and data processing layer on Databricks.
• The Spring Stack: Good experience of Spring Boot, Spring JPA, and Spring Security.
• Modern Java: Deep understanding of functional programming in Java, multithreading, and JVM tuning to support existing code or migrate to Python.
• Cloud Data Warehousing: Hands-on experience with Databricks.
• The AI Edge: Proven exposure to or a deep project-based understanding of working with AI to code using existing Archetypes and rules with all guardrails
• CI/CD - Working with GitHub Actions and workflows for CI/CD