AWS Data Engineer

Project Description:

Our client is a major Australian bank that has a well-established vendor platform managing their trading businesses, and they are looking for an AWS Data Engineer/Associate to join their Reconciliations team.

Our client is looking for a T-shaped professional who is also able to function as BA, test, dev as well and interact with clients. This is a multi-disciplinary role oriented towards end business feature delivery as a consultant. As this role is deeply engrained into the client reconciliation system it will require a developer with at least some reconciliation knowledge.

Responsibilities:

• Collaborate with business stakeholders and technical teams to understand data requirements and implement effective solutions.
• Participate in production support, root cause analysis, and issue resolution for data-related incidents.
• Contribute to the continuous improvement of data architecture, performance, and operational processes.
• Document technical designs, data flows, and operational procedures.
• Work closely with project teams to deliver high-quality solutions within agreed timelines.

Mandatory Skills Description:

• Overall 6-8 years & 5 years of relevant experience.
• AWS Data Engineer or AWS Certified Associate certification/experience is mandatory.
• Hands-on experience with AWS data services such as S3, Glue, Lambda, DynamoDB, Athena, or similar AWS data engineering technologies.
• Strong understanding of data engineering concepts, including ETL/ELT processes, data pipelines, and data integration.
• Good knowledge of SQL, including writing queries, joins, aggregations, and data validation.
• Ability to analyze, troubleshoot, and resolve data-related issues in production and non-production environments.
• Strong analytical and problem-solving skills with attention to detail.
• Good verbal and written communication skills and the ability to collaborate effectively with cross-functional teams.

Nice-to-Have Skills Description:

• Experience working with Intellimatch (reconciliation platform) for financial data reconciliation and exception management.
• Exposure to financial services, capital markets, or investment banking domains.
• Knowledge of data reconciliation processes and controls.
• Familiarity with scripting languages such as Python for automation.
• Understanding of DevOps practices, CI/CD pipelines, and version control tools such as Git.
• Exposure to Agile/Scrum methodologies.
• Good understanding of the trade lifecycle, including trade capture, confirmation, settlement, reconciliation, and reporting.