Expert Software Engineer II

Do you want to shape the future of fintech and healthtech ? Energized by challenges and inspired by bold goals? Ready to elevate your career alongside driven and talented colleagues? If that sounds like you, explore a career at Alegeus today. Opportunity Happens Here .

Expert Software Engineer II

Location: Bangalore, India

Mission

We are looking for an Expert Software Engineer with a strong product mindset and test-driven development (TDD) background to join our consumer-directed healthcare platform engineering team. As a backend application and data-platform developer, you will build Java and Spring Boot microservices and enterprise-scale data capabilities that support reliable data acquisition, ingestion, storage, processing, and consumption. You will provide application-specific business logic as an intermediate layer between front-end experiences, data products, and core platform services.

This role goes beyond writing code to a requirement specification. We need an engineer who understands the business value behind every feature, collaborates closely with product and stakeholders, and takes end-to-end ownership of outcomes. Modern product-minded engineers ask why decisions are made, propose ideas, and build with empathy for users. They contribute to product trade-offs and actively shape what gets built.

Responsibilities

Application and microservice development

• Collaborate on domain decomposition, domain modeling, and domain-driven design (DDD) for new microservices and data domains.

• Design, implement, test, and deploy scalable Java and Spring Boot microservices using RESTful APIs, asynchronous processing, and event-driven patterns.

• Build resilient Kafka-based producers and consumers, including topic design, partitioning, consumer-group management, schema evolution, replay, ordering, and dead-letter handling.

• Use SQL databases and data-access frameworks to create efficient schemas, queries, transactions, indexing strategies, and data lifecycle practices.

• Interface down the stack with legacy APIs and systems where subdomain remapping, data reconciliation, or contract modernization may be required.

• Champion test-driven development and write automated unit, integration, contract, performance, and regression tests.

• Leverage AI-assisted tools for code generation, test-case generation, documentation, and developer productivity.

• Run code reviews, static analysis, and refactoring sessions to improve code quality and maintainability.

• Deploy continuously from local development through staging using CI/CD, with frequent production releases.

• Actively instrument applications and data flows for effective logging, metrics, tracing, alerting, and operational observability.

Enterprise-scale data platform engineering

• Design and evolve data-platform capabilities across the full lifecycle: data acquisition, ingestion, validation, transformation, storage, serving, and consumption.

• Develop reliable ingestion patterns for APIs, events, files, and operational systems, with idempotency, deduplication, replayability, back-pressure, and failure recovery.

• Define data contracts, canonical models, metadata, lineage, quality rules, retention policies, and governance practices in partnership with platform and domain teams.

• Build fit-for-purpose storage and serving patterns using SQL and complementary enterprise data stores as appropriate for transactional, analytical, and operational workloads.

• Enable secure and performant data consumption through APIs, events, query services, reporting interfaces, and downstream data products.

• Design for high availability, scalability, disaster recovery, data security, privacy, and regulatory needs across enterprise data flows.

• Monitor data freshness, completeness, accuracy, throughput, latency, and cost; use these measures to drive continuous improvement.

Product mindset and collaboration

• Actively engage with product managers, product owners, and business stakeholders to understand why features are being built, propose alternative approaches, and weigh engineering and product trade-offs.

• Think beyond the task at hand to deeply understand the purpose and business goals.

• Work cross-functionally with quality assurance, infrastructure, data, security, design, and operations to deliver coherent solutions.

Ownership and accountability

• Take end-to-end ownership for designing, building, and delivering features and data capabilities. Understand that work is not done until a customer or internal consumer has received value.

• Provide ongoing maintenance, support, and enhancements in existing systems, services, and data platforms.

• Communicate progress, raise risks early, and drive resolutions.

Continuous improvement

• Recommend and implement improvements to engineering processes, architecture, data quality, reliability, performance, and cost efficiency.

• Stay current on best practices in Java, Spring Boot, Kafka, SQL, distributed systems, cloud engineering, data platforms, and AI in software engineering.

• Mentor peers on test-driven development, DDD, event-driven architecture, data-platform design, and software craftsmanship.

Education and Experience

Required

• 7+ years of professional software engineering experience at a software product company (building software products sold to businesses or consumers); services or consultancy company backgrounds will only be considered if they involve product engineering in healthcare payments or similar domains.

• Strong test-driven development (TDD) background with demonstrated experience writing unit and integration tests and using test-automation suites.

• Strong proficiency in Java and Spring Boot, including building production-grade REST APIs, microservices, and integrations.

• Hands-on experience with Apache Kafka and event-driven architectures, including resilient producers and consumers, topic design, schema management, and operational troubleshooting.

• Strong SQL experience with relational database design, query optimization, transactions, data modeling, and integration with enterprise data systems.

• Experience designing or contributing to enterprise-scale data platforms covering data acquisition, ingestion, storage, processing, governance, and consumption.

• Experience deploying services to Azure or other cloud platforms and with modern DevOps practices, including CI/CD pipelines, containerization, infrastructure as code, and observability.

• Excellent communication and presentation skills; ability to collaborate across functional areas and translate technical topics into business language.

Preferred qualifications

• Bachelor’s or master’s degree in computer science, engineering, or a related field.

• Experience with cloud-native data services, data lakes or warehouses, stream processing, schema registries, or data-mesh concepts.

• Experience developing applications using micro-frontend architecture and design systems.

• Familiarity with healthcare or payment-processing domains.

• Experience using generative AI for code generation, testing, documentation, and data engineering productivity.

Values The How

At Alegeus, equally important to the “What” — the individual performance goals that each employee commits to in support of the company’s overall success — is the “How,” the framework of principles that guide how we work together to drive our business forward. Overall performance success will also consider individual delivery on our corporate values:

• People First. We pride ourselves in bringing talented people together and treating one another with care. This means we assume best intentions and trust and respect each other. We lift our colleagues up, celebrate diverse perspectives, and accomplish more together.

• Partner Powered. We are committed to empowering our partners, knowing our success is shared and we win as one. This connection drives collaboration across teams and inspires us to continuo