AWS & Java Integration Engineer

Join us as an AWS & Java Integration Engineer at Barclays, where you will spearhead the evolution of our infrastructure and deployment pipelines, driving innovation and operational excellence. You will harness cutting-edge technology to build and manage robust, scalable and secure infrastructure, ensuring seamless delivery of our digital solutions.  

To be successful as an AWS & Java Integration Engineer, you should have experience with:

• Java Development: Strong proficiency in Java, with experience in building enterprise-grade applications or microservices (ideally using frameworks like Spring Boot). Deep understanding of object-oriented design, design patterns, and data structures for robust backend development.
• AWS Cloud Expertise: Hands-on experience deploying and operating services on AWS. This includes building serverless applications with AWS Lambda, designing event-driven architectures, and utilising AWS services for integration tasks (API Gateway, SQS/SNS, etc.). Familiarity with AWS IAM (Identity and Access Management) for secure service access and role permissions is crucial.
• Cloud-Native & Microservices: Knowledge of cloud-native design principles and microservice architecture. Experience creating RESTful APIs, working with containers (Docker) or orchestration (Kubernetes/ECS) for scalable services, and using infrastructure-as-code tools (CloudFormation or Terraform) to manage AWS resources. Ability to implement resilient, fault-tolerant integrations (circuit breakers, retries, monitoring).
• System Integration & IDP: Demonstrated ability to integrate disparate systems and data sources. Experience with enterprise integration patterns (messaging systems, ETL pipelines, SOAP/RESTful services) is important. Additionally, familiarity with Intelligent Document Processing (IDP) solutions on AWS is a plus – for example, understanding how to use services like Amazon Textract or Amazon Bedrock to automate document data extraction and processing. This exposure will help in projects where the bank leverages AI-driven document processing or generative AI services.
• Security & Best Practices: Solid grasp of security practices in development and AWS. Capable of implementing authentication/authorisation, encryption, and secure API design (OAuth, JWTs) in line with banking security standards. Knowledge of logging, monitoring, and testing frameworks (JUnit for Java, and AWS CloudWatch or X-Ray for monitoring) to ensure the integrations are reliable and maintainable.

Some other highly valued skills may include:

• Exposure to AI/ML services or working alongside AI teams is beneficial. This could mean understanding how to integrate machine learning models or AI APIs into applications (for instance, calling a predictive model’s API or incorporating a recommendation engine output into a workflow). Familiarity with AWS’s AI services like Amazon Bedrock (for deploying or consuming foundation models) or Amazon SageMaker would be an advantage. While not a primary responsibility, this knowledge helps in projects where backend systems interface with AI components (such as feeding data to ML models or handling responses from an AI service).
• Domain Knowledge: Experience in the financial services domain is a plus. Understanding banking systems, payment processing, or documents (like loan forms, KYC documents) can help in designing integrations. This domain context will inform better decisions around error handling, data consistency, and compliance when connecting systems.

You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job-specific technical skills.

The role is based out of Pune.

Purpose of the role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation. 

Accountabilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.

Assistant Vice President Expectations

• To advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness. Collaborate closely with other functions/ business divisions.
• Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function. Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives and determination of reward outcomes
• If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others.
• OR for an individual contributor, they will lead collaborative assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will identify new directions for assignments and/ or projects, identifying a combination of cross functional methodologies or practices to meet required outcomes.
• Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
• Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
• Take ownership for managing risk and strengthening controls in relation to the work done.
• Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
• Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
• Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
• Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
• Influence or convince stakeholders to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.