Financial Systems 170381

Job Summary

We are seeking a skilled AWS Data Engineer to join our team, specializing in building, and maintaining modern data pipelines using ETL/ELT methodologies. The ideal candidate will have extensive experience in transforming unstructured data into structured datasets, creating CI/CD automation, and ensuring high-quality, validated data for analytical purposes. Key Responsibilities

Data Pipeline Development: Design, develop, and maintain robust ELT pipelines using databricks.

Data Modeling &

• Transformation: Apply advanced SQL techniques (CTEs, Window functions, joins, aggregations) to build clean, actionable, and scalable data models.

Automation &

• CI/CD: Develop and maintain automated CI/CD deployment pipelines for dbt projects using Git to ensure smooth production deployments.

Data Quality &

• Validation: Perform comprehensive validation between source and target tables, utilizing Q-Test for test case creation, execution, and defect tracking.

Automation: Python scripts for validation and automation.

Version Control: Git, Pull requests, Code reviews.

Data Migration: Hands-on experience with migrating data between heterogeneous systems (Excel, Flat Files, XML, JSON) and SQL servers.

Analytical Skills: Strong problem-solving skills with the ability to adapt quickly in fast-paced environments.

Production Support: Troubleshoot and resolve production issues, data discrepancies, and job failures to ensure data reliability.

Stakeholder Collaboration: Coordinate with business users and stakeholders to gather requirements and translate them into technical solutions.

Documentation: Create technical documentation, demo documents, and wiki pages for all developed jobs and queries.

Preferred

Qualifications

Cloud Platform: AWS

Visualization: Databricks / Oracle PL/SQL (Nice to have) / Oracle EBS AR ( Nice to Have)

Develop and deploy Agentic AI solutions, including autonomous workflows, AI agents, and GenAI-powered automation tools. #QualificationsJob Summary

We are seeking a skilled AWS Data Engineer to join our team, specializing in building, and maintaining modern data pipelines using ETL/ELT methodologies. The ideal candidate will have extensive experience in transforming unstructured data into structured datasets, creating CI/CD automation, and ensuring high-quality, validated data for analytical purposes. Key Responsibilities

Data Pipeline Development: Design, develop, and maintain robust ELT pipelines using databricks.

Data Modeling &

• Transformation: Apply advanced SQL techniques (CTEs, Window functions, joins, aggregations) to build clean, actionable, and scalable data models.

Automation &

• CI/CD: Develop and maintain automated CI/CD deployment pipelines for dbt projects using Git to ensure smooth production deployments.

Data Quality &

• Validation: Perform comprehensive validation between source and target tables, utilizing Q-Test for test case creation, execution, and defect tracking.

Automation: Python scripts for validation and automation.

Version Control: Git, Pull requests, Code reviews.

Data Migration: Hands-on experience with migrating data between heterogeneous systems (Excel, Flat Files, XML, JSON) and SQL servers.

Analytical Skills: Strong problem-solving skills with the ability to adapt quickly in fast-paced environments.

Production Support: Troubleshoot and resolve production issues, data discrepancies, and job failures to ensure data reliability.

Stakeholder Collaboration: Coordinate with business users and stakeholders to gather requirements and translate them into technical solutions.

Documentation: Create technical documentation, demo documents, and wiki pages for all developed jobs and queries.

Preferred

Qualifications

Cloud Platform: AWS

Visualization: Databricks / Oracle PL/SQL (Nice to have) / Oracle EBS AR ( Nice to Have)

Develop and deploy Agentic AI solutions, including autonomous workflows, AI agents, and GenAI-powered automation tools.