Specialist Software Engineer - Java + React

1. Design, develop, and maintain scalable enterprise applications and data engineering solutions using Java, React, Databricks, Apache Spark, and AWS services.
2. Develop responsive, reusable, and high-performance front-end applications using React.js, TypeScript/JavaScript, HTML5, CSS3, and modern UI frameworks.
3. Build and maintain robust backend services, REST APIs, and microservices using Java (Spring Boot) and modern software engineering best practices.
4. Design, develop, and optimize large-scale batch and real-time data pipelines leveraging Databricks, Spark, and cloud-native technologies.
5. Implement ETL/ELT workflows for processing structured, semi-structured, and unstructured data from multiple enterprise data sources.
6. Develop and optimize Spark applications with a focus on performance tuning, partitioning, caching, and resource optimization within Databricks.
7. Build and manage cloud-native solutions on AWS, utilizing services such as S3, Lambda, Glue, EMR, ECS/EKS, Redshift, SNS, SQS, and CloudWatch.
8. Develop data ingestion frameworks, APIs, and integration services to support seamless data and application workflows.
9. Design and implement scalable data models and transformation logic supporting analytics, reporting, and business applications.
10. Work with relational and NoSQL databases, writing complex SQL queries and optimizing database performance.
11. Utilize Delta Lake, Delta Live Tables (DLT), and Unity Catalog to build reliable, secure, and governed data platforms.
12. Develop intuitive dashboards and user interfaces by integrating React applications with backend APIs and enterprise systems.
13. Implement authentication, authorization, and security best practices across frontend, backend, and cloud platforms.
14. Build and maintain CI/CD pipelines using Git, Jenkins, GitHub Actions, Azure DevOps, or similar DevOps tools.
15. Implement Infrastructure as Code (IaC) using Terraform or CloudFormation for automated cloud provisioning and deployments.
16. Develop automated unit, integration, and end-to-end tests for Java services, React applications, and data pipelines.
17. Monitor application, platform, and data pipeline health using logging, observability, and alerting tools.
18. Troubleshoot production issues, perform root cause analysis, and drive continuous improvements in reliability, performance, and scalability.
19. Collaborate with Architects, Product Owners, Data Engineers, UX Designers, and Business Stakeholders to deliver high-quality solutions.
20. Participate in code reviews, architecture discussions, design sessions, and technical decision-making activities.
21. Follow Agile/Scrum methodologies and contribute to sprint planning, estimation, development, testing, and release activities.
22. Ensure compliance with enterprise security, governance, and operational standards.
23. Mentor junior engineers and contribute to technical knowledge sharing and engineering best practices.

Profile Required:
Senior‑level Software Engineer with deep Databricks, AWS, and Java expertise, capable of designing and leading enterprise‑scale AI‑enabled data solutions.

Minimum Qualifications:

• Strong experience in Java 8/11/17, Spring Boot, Spring MVC, and Microservices Architecture.
• Hands-on experience with React.js, JavaScript/TypeScript, Redux/Context API, HTML5, CSS3, and REST API integration.
• Strong expertise in Databricks, Apache Spark, Spark SQL, Delta Lake, and Delta Live Tables (DLT).
• Experience with AWS Cloud Services such as S3, Lambda, Glue, EMR, ECS/EKS, Redshift, CloudWatch, SNS, and SQS.
• Strong knowledge of SQL, database design, and performance optimization.
• Experience developing and consuming RESTful APIs.
• Hands-on experience with Git, Jenkins, CI/CD pipelines, and DevOps practices.
• Experience with Infrastructure as Code using Terraform or CloudFormation.
• Strong understanding of distributed systems, cloud-native architectures, and scalability principles.
• Excellent debugging, troubleshooting, and analytical skills.
• Strong communication and stakeholder management skills.

Preferred Qualifications:

• Experience building and operating AI agents for workflow automation and decision support.
• Strong understanding of data observability, platform reliability, and FinOps practices.
• Experience working in regulated or financial services domains.
• Exposure to enterprise‑scale AI governance, compliance, and audit requirements.
• Ability to influence architecture decisions and align stakeholders.

• Excellent communication skills with both technical and non‑technical audiences.