Data Engineer

Allegiant•Las Vegas, NV

19h•Hybrid

About The Position

The Data Engineer is responsible for architecting, developing, and maintaining Allegiant’s enterprise data infrastructure. The Data Engineer will oversee our transition from on-premise data marts to a cloud hosted warehouse data and develop the next generation of our data tools. Visa Sponsorship Available: No Minimum Requirements Combination of Education and Experience will be considered. Must be authorized to work in the US as defined by the Immigration Act of 1986. Must pass a Criminal Background Check. Education: Bachelor’s Degree In Computer Science, Engineering, or a related technical field. Years of Experience: Minimum three (3) years of experience as a Data Engineer which includes work experience in data mart development and data warehousing, including experience working with ETL processes, OLAP structures, and dimensional modeling. Strong SQL Server and Amazon Redshift skills. In depth understanding of database architecture. Demonstrated basic proficiency in AWS services, including but not limited to S3, Glue, Lambda, and Redshift. Basic understanding of Infrastructure as Code (IAC) principles to define and manage infrastructure using code (e.g., AWS CloudFormation, Terraform). Manage time effectively to meet deadlines across multiple projects. Excellent critical thinker and effective problem solver with creative solutions. Detail oriented and highly organized. Results-driven; accepting responsibility for individual performance and contributions to team projects. Ability to work a hybrid schedule with the expectation to be in the office 2 days a week or 8 days a month (when campus is open) and to work the remainder remotely. Must be able to work in a high pressure environment. Must have sufficient vision and ability to safely perform the essential functions of the position.

Requirements

Must be authorized to work in the US as defined by the Immigration Act of 1986.
Must pass a Criminal Background Check.
Bachelor’s Degree In Computer Science, Engineering, or a related technical field.
Minimum three (3) years of experience as a Data Engineer which includes work experience in data mart development and data warehousing, including experience working with ETL processes, OLAP structures, and dimensional modeling.
Strong SQL Server and Amazon Redshift skills.
In depth understanding of database architecture.
Demonstrated basic proficiency in AWS services, including but not limited to S3, Glue, Lambda, and Redshift.
Basic understanding of Infrastructure as Code (IAC) principles to define and manage infrastructure using code (e.g., AWS CloudFormation, Terraform).
Manage time effectively to meet deadlines across multiple projects.
Excellent critical thinker and effective problem solver with creative solutions.
Detail oriented and highly organized.
Results-driven; accepting responsibility for individual performance and contributions to team projects.
Ability to work a hybrid schedule with the expectation to be in the office 2 days a week or 8 days a month (when campus is open) and to work the remainder remotely.
Must be able to work in a high pressure environment.
Must have sufficient vision and ability to safely perform the essential functions of the position.

Nice To Haves

Python development skills.

Responsibilities

Develop and maintain Allegiant data marts and data warehouses.
Migrate Allegiant’s existing on-premise infrastructure to the AWS environment.
Design, implement, and maintain scalable ETL processes to ensure efficient data flow and accessibility.
Implement data quality checks to ensure accuracy and reliability of data.
Troubleshoot and resolve issues related to data processing and ETL pipelines.
Design, build, and implement data transformation, conversion, and validation of data required for BI applications.
Maintain SQL Server and Redshift data marts, databases, and data warehouses.
Provide services to replicate data from various data sources to reporting database servers for enterprise reporting applications.
Work closely with the business to understand and translate user requirements into practical data models.
Develop and maintain repeatable, systemic processes while finding ways to make internal team processes more efficient.
Other duties as assigned.