Data Engineer

• Design, build, and maintain scalable and reliable data pipelines through ELT/ETL extraction methods.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and ensure data quality
• Develop and maintain documentation, including data dictionaries, workflow diagrams, and data flow diagrams
• Ensure the integrity and security of data by implementing appropriate controls and monitoring
• Optimize and tune data pipelines to ensure efficient processing and query performance
• Implement and maintain data security policies and procedures, including access controls, encryption, and data masking
• Design and implement data processing workflows using dbt and Prefect to support data science and machine learning applications
• Develop and maintain data ingestion processes to bring data from external sources into the organization’s data environment
• Identify and address performance issues with data pipelines, and work with infrastructure and operations teams to optimize system performance
• Conduct testing and validation of data pipelines to ensure they are functioning correctly and meeting business requirements
• Participate in code reviews and contribute to the development of best practices for data engineering
• Stay current with emerging technologies and trends in data engineering and data science, and identify opportunities to leverage them within the organization

Do you have experience in Version control systems?, Do you have a Master’s degree?, * Bachelor’s or Master’s degree in Data Science, Information Systems, or a related field

• 3+ years building and maintaining production data pipelines (degree in a related field or equivalent experience)
• Advanced SQL: window functions, CTEs, and query/performance tuning on large datasets
• Strong Python for data engineering (modular, testable pipeline code)
• Hands-on dbt experience: models, tests, macros, and incremental materializations
• Production Snowflake experience: schema design, performance tuning, and warehouse/cost optimization
• AWS data services (e.g., S3, Glue, Lambda)
• Data quality and observability with dbt + Elementary
• Infrastructure-as-code with Terraform and version control with Git
• Dimensional data modeling (star/snowflake schemas, SCDs) and lakehouse concepts
• Strong problem-solving skills and clear communication with analysts, scientists, and stakeholders

Pulled from the full job description

• Paid parental leave
• Parental leave
• Health insurance
• 401(k) matching
• Paid time off
• Vision insurance
• Dental insurance, Medical, dental, and vision benefits
• 15 days PTO/year
• 10 paid holidays
• Paid parental leave
• Personal phone bill reimbursement
• Gym reimbursement
• Corporate DoorDash® DashPass membership
• Regular company and team activities
• 401k with competitive matching contribution plan
• Excellent opportunities for career growth
• Work in a hyper-growth company

Crumbl was founded in 2017 by Jason McGowan & Sawyer Hemsley in Logan, Utah. It is now the fastest-growing cookie company in the nation with over 1000 locations in the USA and Canada. Crumbl is powered by cutting-edge technology, iconic branding, delicious desserts, and passionate people. Crumbl HQ and franchisees provide employment for over 26,000 people across the United States, and all of our franchises are owned and operated by independent members of the local community. Crumbl’s 200+ unique cookie flavors rotate weekly and are served in our famous pink box! Crumbl is an equal opportunity employer. Crumbl provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, national origin, sexual orientation, gender identity or expression, age, disability, genetic information, marital status or veteran status. Recruitment Agencies: Crumbl HQ doesn’t typically partner with 3rd party recruitment resources. If we require assistance on this search we will contact selected partners directly; we do not accept unsolicited candidate submissions. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.