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 up-to-date 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.
📌 Financial Systems 170381 (Telangana)
🏢 ADP
📍 Telangana