Java Developer – Spring Boot, Microservices, Big Data & Cloud

Job Summary Synechron is seeking a Java Developer with strong experience in Java, multithreading, database concepts, microservices, and Spring Boot. The role focuses on developing scalable, data-driven solutions, supporting efficient data processing, and contributing to the design and maintenance of data pipelines.The successful candidate will collect, analyze, and interpret large datasets; translate business requirements into technology solutions; and collaborate with cross-functional teams to support informed, data-driven decision-making. This position contributes to business objectives by improving data accessibility, processing efficiency, solution reliability, and the quality of analytical insights.

Software Requirements Required Proficiency in Java, with approximately 4–5 years of hands-on development experience.

Practical knowledge of multithreading, concurrency, and performance optimization in Java applications.

Strong understanding of database concepts, including data modeling, querying, indexing, transactions, and performance considerations.

Experience developing microservices using Spring Boot.

Experience designing, developing, and maintaining data pipelines for efficient data processing.

Experience collecting, analyzing, and interpreting large datasets to identify trends and insights.

Working knowledge of cloud-based data storage and processing solutions using AWS and Google Cloud Platform.

Familiarity with big data technologies, including Hadoop and Spark.

Experience troubleshooting application, data-processing, integration, and production issues.

Ability to work with current, supported versions of Java, Spring Boot, databases, and related development tools.

Preferred Experience building and supporting distributed, high-volume data-processing applications.

Experience with Java 11 or later and current long-term-support Java versions.

Exposure to containerized microservices, RESTful APIs, event-driven systems, and cloud-native application development.

Experience with cloud data storage, data-processing, and monitoring services.

Familiarity with automated testing, continuous integration, continuous delivery, and infrastructure automation.

Experience in finance, healthcare, technology, or another data-intensive industry.

A recognized certification in data, analytics, cloud, or data science.

Overall Responsibilities Collect, analyze, and interpret large datasets to identify trends, patterns, risks, and actionable insights.

Design and implement data-driven solutions that address business and operational problems.

Develop, enhance, and maintain scalable Java-based microservices using Spring Boot.

Apply multithreading and concurrency concepts to improve application performance, responsiveness, and reliability.

Develop and maintain data pipelines that support efficient, accurate, and traceable data processing.

Work with databases and cloud-based data storage solutions to support data access, integration, and analysis.

Use Hadoop, Spark, and related technologies where appropriate for large-scale data processing.

Collaborate with business, technology, data, and other departments to understand data requirements and deliver appropriate solutions.

Investigate and resolve software, data-quality, integration, and performance issues.

Contribute to technical design discussions, code reviews, testing, documentation, and production support.

Stay current with relevant industry trends, data practices, software engineering methods, and cloud technologies.

Support sustainable technology practices by promoting efficient data processing, appropriate resource utilization, reusable components, and responsible use of cloud infrastructure.

Deliver maintainable solutions that meet agreed requirements, quality standards, performance expectations, and delivery timelines.

Technical Skills (By Category) Programming Languages

Essential

Java with practical experience in object-oriented programming, collections, exception handling, concurrency, and multithreading.

Ability to write readable, maintainable, testable, and production-ready code.

Strong understanding of Java application performance and troubleshooting.

Preferred

Experience with scripting languages used for data processing or automation.

Exposure to programming approaches used in distributed and data-intensive applications.

Databases/Data Management Essential

Strong understanding of database concepts, including relational data modeling, SQL, joins, indexing, transactions, normalization, and query performance.

Experience integrating Java applications with databases.

Ability to analyze data quality, structure, completeness, and consistency.

Experience developing or supporting data pipelines for reliable data movement and processing.

Preferred

Experience with large-scale or distributed data stores.

Familiarity with data warehousing, data lakes, batch processing, and streaming data.

Exposure to data governance, metadata management, lineage, and data-quality controls.

Cloud Technologies Essential

Experience with cloud-based data storage solutions on AWS and Google Cloud Platform.

Understanding of cloud-based application deployment, data access, permissions, and resource management.

Ability to apply basic cloud security, availability, scalability, and cost-efficiency considerations.

Preferred

Experience with cloud-native data-processing services.

Familiarity with containers, orchestration, logging, monitoring, and cloud-based application integration.

Experience applying sustainable cloud practices, including efficient resource use and appropriate storage and processing choices.

Frameworks and Libraries Essential

Spring Boot for developing and maintaining microservices.

Familiarity with Spring-based application development, dependency injection, configuration, and service integration.

Experience designing and consuming RESTful APIs.

Experience using testing frameworks and practices appropriate for Java applications.

Preferred

Exposure to Spring Cloud or comparable tools for distributed application development.

Familiarity with messaging, event-driven architecture, and API documentation tools.

Experience with libraries or frameworks used for big data processing and analytics.

Development Tools and Methodologies Essential

Experience with source control, code review, defect tracking, build processes, and automated testing.

Understanding of software development life cycle practices, Agile delivery, and iterative development.

Ability to create technical documentation and support knowledge sharing.

Experience diagnosing performance, integration, and production issues.

Preferred

Experience with continuous integration and continuous delivery pipelines.

Familiarity with containerization, infrastructure automation, and application monitoring.

Experience working with data analysis, visualization, or operational reporting tools.

Exposure to automated quality checks, static analysis, and performance testing.

Security Protocols Essential

Understanding of secure coding practices for Java and microservices.

Awareness of authentication, authorization, access controls, encryption, secure API design, and protection of sensitive data.

Ability to follow organizational security, privacy, compliance, and data-handling standards.

Preferred

Experience implementing role-based access controls and secure service-to-service communication.

Familiarity with security testing, vulnerability remediation, audit requirements, and cloud security controls.

Experience Requirements 4–5 years of professional experience in data analysis, data-driven decision-making, software development, or a related role.

Demonstrable experience developing Java applications, microservices, and Spring Boot solutions.

Practical experience with multithreading, database concepts, data pipelines, and large-scale data processing.

Experience analyzing datasets and converting findings into technical or business solutions.

Experience collaborating with departments or stakeholders to understand data requirements and deliver data-driven outcomes.

Experience in finance, healthcare, technology, or another relevant industry is preferred.

Candidates may qualify through equivalent practical experience, relevant technical training, demonstrable project work, or a combination of education and professional experience.

Experience should be assessed based on relevant outcomes, technical capability, and the ability to perform the responsibilities of the role.

Day-to-Day Activities Collect, analyze, and interpret large datasets; develop Java and Spring Boot services; and design or maintain data pipelines for efficient processing.

Participate in requirements discussions, technical planning, code reviews, testing activities, and collaboration with business, data, and technology teams.

Deliver maintainable code, technical documentation, data-processing improvements, analytical outputs, and timely resolutions to application or data issues.

Make day-to-day technical decisions within assigned responsibilities, escalate risks appropriately, and ensure solutions meet requirements for quality, security, performance, and sustainability.

Qualifications Bachelor's degree in Computer Science, Information Technology, Data Science, or a related field; equivalent relevant professional experience may also be considered.

Recognized certification in data or analytics, such as Certified Analytics Professional, is preferred.

A recognized cloud data-science or cloud analytics certification at an equivalent level is preferred.

Completion of relevant training in Java, Spring Boot, microservices, databases, big data, cloud technologies, or data analytics is beneficial.

Maintain continuous professional development by staying current with Java, data engineering, analytics, cloud platforms, security practices, and industry standards.

Professional Competencies and Soft Skills Apply critical thinking, analytical reasoning, and structured problem-solving to investigate issues and make data-driven decisions.

Collaborate effectively with technical and non-technical stakeholders and contribute constructively to team objectives.

Communicate technical information, findings, risks, and recommendations clearly through written and verbal communication.

Adapt to changing requirements, technologies, delivery priorities, and work environments while maintaining reliable outcomes.

Identify opportunities to improve data solutions, application quality, processing efficiency, and sustainable use of technology.

Prioritize and manage multiple tasks in a fast-paced, high-pressure environment while maintaining a customer-focused approach, a positive work ethic, and accountability for deliverables.

S​ YNECHRON’S DIVERSITY & INCLUSION STATEMENT   Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law .

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