SQL ETL Developer — AWS Data Pipelines & Spark

Quantum Technologies. LLC; Greenwood Village (CO); Sur place; USD 100 000 - 140 000; Plein temps

Résumé du poste

Quantum Technologies. LLC is seeking a data engineer to design, develop, and maintain complex ETL transformations using advanced SQL in an AWS-based environment.

You will optimize SQL transformations with CTEs and window functions, work on large datasets, and collaborate across distributed teams to ensure data quality and reliable pipelines using Python, shell scripts, and Spark where applicable. This role emphasizes performance tuning, production-grade ETL, and adaptability in a fast-paced,

Qualifications

• Strong, hands-on experience with advanced SQL, including CTEs and window functions.
• Proven experience working with large datasets at scale.
• Experience performing ETL transformations in production environments.
• Familiarity with AWS data services, particularly Athena and/or EMR.
• Ability to work in an agile environment with shifting priorities and multiple workstreams.

Responsabilités

• Design, develop, and maintain complex ETL transformations using advanced SQL.
• Process and transform large-scale datasets efficiently.
• Build and optimize SQL-based data transformations leveraging CTEs and window functions.
• Support and enhance data pipelines running in an AWS-based environment.
• Work with SQL-driven Spark workloads where applicable.
• Utilize template-based shell and Python scripts to support ETL workflows.
• Collaborate across distributed teams to support evolving data needs and priorities.
• Troubleshoot performance and data quality issues across ETL processes.

Connaissances

Advanced SQL

CTEs

Window functions

Large-scale data

Outils

AWS (Athena/EMR)

ETL pipelines

Python scripting

Shell scripting

Spark

Description du poste

Quantum Technologies. LLC is seeking a data engineer to design, develop, and maintain complex ETL transformations using advanced SQL in an AWS-based environment.

You will optimize SQL transformations with CTEs and window functions, work on large datasets, and collaborate across distributed teams to ensure data quality and reliable pipelines using Python, shell scripts, and Spark where applicable. This role emphasizes performance tuning, production-grade ETL, and adaptability in a fast-paced,