Offer summary

Qualifications:

4+ years of experience in cloud-based data warehouse environments, preferably AWS., Expert-level proficiency in SQL and Python., Hands-on experience with Amazon Redshift, Apache Airflow, and Amazon QuickSight., Deep understanding of data modeling and performance optimization..

Key responsibilities:

Architect and maintain a cloud-native data warehouse infrastructure on AWS.

Design and implement efficient data models in Amazon Redshift.

Build and monitor Airflow DAGs for automated ETL/ELT workflows.

Develop dashboards in Amazon QuickSight for key business metrics.

Job description

At Aluxion we are seeking a seasoned Data Warehouse Engineer with deep expertise in AWS-based analytics infrastructure. In this role, you will design, build, and optimize a robust data platform that supports critical business insights and scalable operations.

You’ll take full ownership of our analytics stack working daily with Amazon Redshift for advanced data modeling and performance tuning, orchestrating ETL/ELT workflows using Apache Airflow, and building clear, actionable dashboards in Amazon QuickSight. You'll also work with DynamoDB, EventBridge, and S3 for auxiliary data flows and event-driven triggers.

Job Details:

100% remote job
Full time
Long term

Key Responsibilities

Architect and maintain a cloud-native data warehouse infrastructure on AWS
Design and implement efficient and scalable data models in Amazon Redshift
Build and monitor Airflow DAGs for reliable and automated ETL/ELT workflows
Develop dashboards and visualizations in Amazon QuickSight for key business metrics
Integrate AWS services like DynamoDB, S3, and EventBridge to support real-time and batch data flows
Collaborate with cross-functional teams to define data requirements and ensure data availability
Monitor system performance and cost, continuously optimizing for efficiency
Ensure high standards of data quality, security, and operational reliability

Qualifications

4+ years of experience working in cloud-based DWH environments (AWS preferred)
Expert-level proficiency in SQL and Python
Hands-on experience with Amazon Redshift, Apache Airflow, Amazon QuickSight, S3, DynamoDB, and EventBridge
Deep understanding of data modeling, data warehousing principles, and performance optimization
Familiarity with CI/CD pipelines and infrastructure as code practices
Proactive mindset with a focus on data integrity, cost control, and resilient operations
Excellent communication skills and a collaborative, ownership-driven attitude