Aws Data Engineer

**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:

AWS Developer

AWS Glue

AWS Lambda

AWS S3

SQL

**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.