Java Technical Lead

Job Title

Pay Range: $56hr - $61hr

Requirement/Must Have:

• Java Development – 10+ years.
• Spring Boot & Microservices – 8+ years.
• REST API Development – 8+ years.
• AWS Cloud (S3, IAM, Security Fundamentals) – 6+ years.
• AWS Glue (Jobs, Crawlers, Workflows) – 4+ years.
• ELT/Data Ingestion Pipelines – 4+ years.
• Apache Iceberg (Schema Evolution, Partitioning, Compaction) – 2+ years.
• Oracle Database / Aurora MySQL – 8+ years.
• MongoDB – 3+ years.
• CI/CD, Git, Maven/Gradle, Automated Testing – 5+ years.
• Technical Leadership (Architecture, Code Reviews, Mentoring) – 3+ years.
• Production Support & Troubleshooting – 5+ years.

Responsibilities:

• Lead the design and development of microservices and REST APIs using Java and Spring Boot.
• Define API contracts, implement business logic, validations, standardized error handling, and logging.
• Apply resiliency patterns (timeouts, retries, circuit breakers, idempotency) and drive performance improvements.
• Conduct code reviews, enforce engineering standards, and mentor team members.
• Build and operate services on AWS, following security and operational standards (IAM basics, networking awareness, observability).
• Support CI/CD, release activities, and production troubleshooting.
• Design and optimize data access with Oracle Aurora MySQL and MongoDB.
• Perform query tuning/indexing guidance and improve service performance and reliability.
• Work with file and table-based data in Amazon S3 (folder/partition design, access controls, encryption, lifecycle).
• Support ELT pipelines using AWS Glue (jobs, crawlers, workflows) for ingestion, transformation, and standardization.
• Design and work with Apache Iceberg tables (schema evolution, partitioning, table properties, compaction/maintenance patterns).
• Collaborate with data engineering and analytics teams to enable consumption via Athena/Glue Data Catalog (and related query engines).
• Troubleshoot data pipeline issues (permissions, catalog/table visibility, schema mismatches, performance bottlenecks).
• Integrate services with existing ML inference endpoints; validate payloads and handle model-driven response patterns.
• Support controlled rollouts for model-dependent features in coordination with ML teams.

Nice to Have:

• Athena optimization experience (partition pruning, Iceberg maintenance/compaction strategy).
• Kafka/event streaming.
• Docker/Kubernetes (EKS) or ECS.
• Observability tools: CloudWatch, Client /ELK, Prometheus/Grafana, OpenTelemetry.
• Python for scripting/automation.
• Security: OAuth2/OIDC, JWT, OWASP, Secrets Manager/Parameter Store.
• Infrastructure as Code: Terraform/CloudFormation.

Qualification And Education:

• Strong experience in Java and Spring Boot building production APIs/microservices.
• Strong AWS experience including S3 and security fundamentals (IAM, encryption, least privilege).
• Hands-on experience with AWS Glue and ELT/data ingestion patterns.
• Working knowledge of Apache Iceberg tables (or strong experience with lakehouse table formats).
• Strong database experience with Oracle/Aurora MySQL, plus knowledge of MongoDB.
• Experience with CI/CD, Git, Maven/Gradle, and automated testing.
• Strong troubleshooting and communication skills; ability to lead design discussions.