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# AWS - DB Hands-on Architect

- **Company:** Coeus Logix LLC
- **Location:** Irving, TX, United States
- **Contract:** Contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Big Data, Computer Programming, Databases, Data Integrity, Extract Transform Load (ETL), Python (Programming Language), PostgreSQL, SQL Stored Procedures, Data Processing, Data Storage Technologies, Apache Spark, Database Performance, Data Lakes, Data Pipelines
- **Published:** November 5, 2026
- **Apply:** https://www.dice.com/job-detail/ac00bf01-bad5-4a28-b6e2-f4f6f2f83a88

## About the Role

This role requires a blend of hands-on technical skills and strategic thinking to ensure our database systems are robust, scalable, and efficient., * Proficiency in Amazon S3 for data storage and management.

 * Experience with AWS Glue ETL for data processing and transformation.
 * Strong programming skills in Python, with a focus on database operations.
 * Experience with Apache Spark for large-scale data processing.
 * Knowledge of Apache Airflow and AWS Step Functions for data orchestration.
 * Expertise in PostgreSQL database design, development, and management.
 * Familiarity with Iceberg for data lake management.
 * Ability to create and manage dashboards and reports for data insights.
 * Experience working with large databases and handling large volumes of data.

<>Preferred Skills

 * Experience with DB archival processes.
 * Knowledge of stored procedures and their implementation.
 * Familiarity with data orchestration tools and practices.
 * Strong analytical skills to manage and optimize database performance.
 * Excellent communication and collaboration skills to work effectively with cross-functional teams.

## Description

* Design and develop database tables, ensuring they are optimized for performance and scalability.
 * Implement and manage data orchestration processes using tools such as Apache Airflow and AWS Step Functions.
 * Develop and maintain stored procedures to enhance database functionality and efficiency.
 * Perform database archival processes to manage data lifecycle effectively.
 * Utilize AWS services such as Amazon S3, Glue ETL, and PostgreSQL to build and manage data pipelines.
 * Work with large volumes of data, including billions of rows, to ensure data integrity and performance.
 * Implement Extract, Transform, Load (ETL) processes using Apache Spark and Python.
 * Create and manage dashboards and reports to provide insights into database performance and data quality.
 * Collaborate with cross-functional teams to ensure database solutions align with business objectives.