We are looking for a Software Engineer to join our post-trade technology team, working on data-driven products and services that support high-volume transaction processing, analytics, reporting, and internal business workflows.

The ideal candidate will be comfortable building and maintaining production-grade software across data pipelines, microservices, and cloud-hosted systems. This role requires strong engineering fundamentals, a pragmatic approach to system design, and the ability to work closely with product managers, data scientists, and business stakeholders to deliver reliable, scalable data products.

The successful candidate will help develop and operate systems processing hundreds of thousands of transactions per hour and millions of records per day, with a focus on correctness, performance, observability, and maintainability. Experience with Python data tooling particularly Pandas is key, alongside strong backend engineering capability in Java and Spring Boot.

Key Responsibilities

- Design, build, and maintain cloud-hosted data products and microservices supporting post-trade workflows.
- Develop data pipelines capable of processing high-volume transaction datasets, including extraction, transformation, enrichment, and validation logic.
- Use Pandas, SQL, and related data tooling to implement complex business transformations and support data analysis.
- Build and maintain backend services using Java, Spring Boot, and associated microservice patterns.
- Take ownership of data quality, data lineage, and technical investigation of business queries.
- Collaborate with product managers, data scientists, analysts, and other engineers to define technical architecture and implementation plans.




- Contribute to system design decisions that improve scalability, reliability, and operational resilience.
- Implement observability through metrics, dashboards, alerts, and logging, ensuring services meet agreed SLAs.
- Support cloud-native deployments and infrastructure using technologies such as Docker, Kubernetes, Jenkins, or equivalent platforms.
- Contribute to engineering standards, testing practices, documentation, and code quality across the team.
- Participate in Agile delivery ceremonies, code reviews, incident investigations, and continuous improvement activities.

Required Skills and Experience

- Strong software engineering experience in production environments.
- Hands-on experience building data-driven applications, data pipelines, or analytics-oriented services.
- Strong Python experience, particularly with Pandas for data transformation and analysis.
- Experience with Java and Spring Boot for backend microservices development.
- Good understanding of SQL and working with large datasets.
- Experience designing and operating microservices in cloud or containerised environments.
- Familiarity with CI/CD, automated testing, monitoring, and production support.
- Ability to reason about data quality, edge cases, performance, and operational failure modes.
- Strong communication skills,



with the ability to work directly with technical and non-technical stakeholders.

Desirable Skills

- Experience with AWS services such as S3, Athena, ECS, EC2, Lambda, or SageMaker.
- Experience with observability tooling such as Datadog.
- Exposure to container platforms such as Kubernetes.
- Experience with MongoDB or other NoSQL databases.
- Familiarity with testing frameworks such as PyTest and JUnit.
- Experience optimising cloud infrastructure or compute costs.
- Exposure to financial services, post-trade systems, regulatory reporting, or transaction analytics.

Strong Plus

- Experience with AI/ML, including building models, supporting data science workflows, or deploying machine learning proof-of-concepts.
- Hands-on experience with GenAI projects, particularly for internal tooling, support automation, and business productivity.
- Experience developing ML models for anomaly detection, outlier detection, forecasting, classification, or transaction monitoring.

Candidate Profile

This role would suit an engineer who enjoys working close to the data, understands that data correctness is as important as code quality, and is comfortable taking ownership of production systems. The ideal candidate combines strong backend engineering skills with practical data engineering experience and can bridge the gap between software development, analytics, and business-facing technical support.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Software Engineer Post-Trade Data Products (Hubballi)
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