Java Big Data architect

Role Summary

We are seeking a highly skilled and experienced personnel to join our team. The successful candidate will be instrumental in designing, developing, and evolving our modern data platform with a strong emphasis on self-service capabilities, data management compliance, and robust governance. This role requires a hands-on individual who can translate product vision into high-level architectural designs and detailed technical solutions, while also providing technical leadership and guidance to development teams.

Key Responsibilities

• Architectural Design: Understand the product vision and roadmap to create corresponding high-level architectural designs, and subsequently translate these into detailed solutions for specific features during EPIC grooming sessions.
• Technical Leadership & Guidance: Guide development leads and engineers through the development lifecycle, ensuring adherence to architectural principles and best practices.
• Quality Assurance
  
  Collaboration:
  
  Collaborate with functional and performance testing teams to define appropriate test strategies and scenarios. Review test results and insights to continuously improve design and code quality.
• User Feedback Integration: Actively review feedback from users regarding new features or challenges, incorporating insights into future design iterations and improvements.
• Hands-on Development & Troubleshooting: Serve as a fully hands-on Data Engineer, capable of diving into code to identify and resolve issues, bottlenecks, and performance challenges.
• Resilient Solution Development: Design and build highly resilient, scalable, and observable modern data solutions that meet business requirements.

Required Skills and Experience

• Programming & Frameworks: Master-level experience with Java Spring Boot framework.
• Container Orchestration: Strong expertise with Kubernetes for deploying and managing data platform components.
• Big Data Technologies: Extensive experience in handling Big Data with a strong background in Spark and Scala.
• Streaming Platforms: Proficient in Kafka and streaming technologies, including advanced features such as schema registry and data quality implementation.
• Observability: Hands-on experience with observability stacks, particularly Grafana, for monitoring and gaining insights into data platform performance.
• Solution Design: Proven ability to design and implement highly resilient and scalable modern data solutions.
• Problem Solving: Excellent analytical and problem-solving skills, with a keen eye for identifying and rectifying technical issues.
• Communication: Strong communication skills, capable of articulating complex technical concepts to both technical and non-technical stakeholders.