Java Architect (Data Engineering) [ Need minimum 14+ Years experience after Graduation/Bachelors ]

• Title :- Java Architect (Data Engineering)
• Location :- Charlotte, NC
• Minimum Experience :- Overall minimum 12+ years of professional software engineering experience.

• Role Summary
• An experienced Java Architect to lead the design and delivery of scalable, distributed backend systems, combining strong Java/Spring Boot architecture skills with hands-on data engineering expertise across streaming and batch pipelines.

• Key Responsibilities
• Architect and design enterprise-grade Java/Spring Boot applications and microservices
• Design and oversee distributed, cloud-native systems for scalability, resilience, and performance
• Architect data engineering solutions including streaming pipelines (Kafka), batch processing (Spark), and ETL/ELT workflows
• Guide data lake/data warehouse design and integration strategy
• Provide technical leadership and architectural direction across engineering teams
• Ensure best practices in system design, code quality, and cloud deployment

• Required Skills
• Strong hands-on expertise in Java, Spring Boot, and microservices architecture.
• Experience designing and operating distributed systems.
• Hands-on Data Engineering experience (pipelines, data processing, integration).
• Proven architecture and technical leadership capability.

Years of Experience

• Overall minimum: 10–12+ years of professional software engineering experience.
• A rough breakdown of how that experience is usually expected to be distributed:
• 08 - 10+ years in core Java development, with a good chunk of that in Spring Boot/microservices architecture specifically (not just using it, but designing systems with it).
• 04 -06+ years in an architect or senior technical lead capacity - designing systems, making technology decisions, mentoring teams, not just implementing tickets.
• 03 - 05+ years of hands-on distributed systems / cloud experience (AWS/Azure/GCP), including scalability, resilience, and deployment concerns.
• 02 - 04+ years of hands-on data engineering work, Kafka, Spark, ETL/ELT pipelines, and data lake/warehouse design.

• Preferred Skills
• Kafka (streaming/event-driven architecture).
• Apache Spark (large-scale data processing).
• ETL/ELT pipeline design and implementation.
• Data lake / data warehouse architecture.
• Cloud platform experience: AWS, Azure, and/or GCP (multi-cloud a plus).

Ideal Candidate Profile: Senior-level engineer/architect with a blend of core Java backend architecture skills and practical data engineering experience, comfortable leading technical direction across cloud and distributed data systems.