Data Engineer

Allegiant•Minneapolis, MN

55d•$87,000 - $124,700•Hybrid

About The Position

The Data Engineer is responsible for architecting, developing, and maintaining Allegiant’s enterprise data infrastructure. The role will oversee the transition from on-premise data marts to a cloud-hosted data warehouse and develop the next generation of data tools. The position works on a hybrid schedule, with an expectation to be in the office two days a week or eight days a month when campus is open and to work remotely the remainder of the time. The role may involve working in a high-pressure environment and supporting Allegiant’s essential services during declared national or state emergencies, when team members may be required to report to their assigned work location unless prohibited by government order. The position requires at least three years of Data Engineer experience, including data mart development and data warehousing, and a bachelor’s degree in computer science, engineering, or a related technical field. Candidates must be authorized to work in the United States and pass a criminal background check. Python development skills are preferred. The salary range is $87,000–$124,700 per year. The role is based in an office/IT environment and includes regular use of a computer, keyboard, printer, and phone. Physical requirements and working conditions may include standing, sitting, talking, hearing, seeing, reaching, stooping, kneeling, operating equipment with hands and fingers, lifting, pushing, pulling, or carrying up to 50 pounds, working in a confined area, and sitting at a computer terminal for extended periods. The role may require various shifts or days in a 24-hour situation, regular attendance, and some travel. The work environment may involve moderate office noise and fluctuations in temperature and lighting. Reasonable accommodations may be made for individuals with disabilities.

Requirements

Bachelor’s degree in computer science, engineering, or a related technical field.
At least three years of experience as a Data Engineer, including data mart development and data warehousing.
Experience working with ETL processes, OLAP structures, and dimensional modeling.
Strong SQL Server and Amazon Redshift skills.
In-depth understanding of database architecture.
Basic proficiency in AWS services, including services such as S3, Glue, Lambda, and Redshift.
Basic understanding of Infrastructure as Code principles and defining and managing infrastructure using code, such as AWS CloudFormation or Terraform.
Ability to manage time effectively and meet deadlines across multiple projects.
Critical-thinking and problem-solving skills, including developing 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: in the office two days a week or eight days a month when campus is open, and remotely the remainder of the time.
Ability to work in a high-pressure environment.
Sufficient vision and ability to safely perform the essential functions of the position.
Must be authorized to work in the United States as defined by the Immigration Act of 1986.
Must pass a criminal background check.

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 data accuracy and reliability.
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 and identify ways to make internal team processes more efficient.
Perform other duties as assigned.