We are seeking a highly skilled and experienced professional to join our team as a Java with Big Data Architect. The successful candidate will play a critical role in designing, developing, and evolving our modern data platform with a strong emphasis on self-service capabilities, compliance, and governance. This role requires a hands-on architect who can transform product vision into scalable designs and detailed technical solutions while providing leadership and technical guidance to development teams.

REQUIRED SKILLS AND EXPERIENCE

• Programming & Frameworks: Master-level experience with Java and Spring Boot.
• Container Orchestration: Expertise with Kubernetes for deploying and managing platform components.
• Big Data Technologies: Strong hands-on experience with Big Data, including Spark and Scala.
• Streaming Platforms: Proficiency in Kafka and streaming technologies, including schema registry and data quality implementation.
• Observability: Hands-on experience with Grafana and observability stacks for monitoring platform performance.
• Solution Design: Proven track record of designing and implementing scalable, resilient, and modern data solutions.
• Problem Solving: Strong analytical and troubleshooting skills to quickly identify and resolve technical challenges.
• Communication: Excellent communication skills to present complex technical concepts to technical and non-technical stakeholders.
  Job Type: Full-time
  Pay: $150,000.00-$155,000.00 per year

Application question(s):

• This is a Full-Time position, are you still interested in applying for this role?
• Please share your LinkedIn profile. (Mandatory requirement)

Experience:

• Big Data Architect: 8 years (preferred)

• Architectural Design: Translate product vision and roadmap into high-level designs and detailed technical solutions during EPIC grooming sessions.
• Technical Leadership & Guidance: Provide direction to development leads and engineers, ensuring adherence to architectural standards and best practices.
• Quality Assurance Collaboration: Work with QA teams to define test strategies, review results, and drive continuous improvements in design and code quality.
• User Feedback Integration: Incorporate user feedback into design iterations to enhance platform features and resolve challenges.
• Hands-on Development & Troubleshooting: Act as a hands-on Data Engineer, resolving performance bottlenecks and technical issues.
• Resilient Solution Development: Design and implement scalable, resilient, and observable modern data solutions that meet evolving business needs.