Data Engineer

Based at Crumbl HQ in Provo, Utah, this Data Engineer role focuses on designing, building, and maintaining scalable data pipelines with dbt and Prefect to support data-driven decision making across the organization.

Responsibilities

• Design, implement, and maintain scalable data pipelines using ELT/ETL extraction methods to ensure reliability.
• Collaborate with data scientists, analysts, and other stakeholders to capture data requirements and uphold data quality.
• Create and maintain documentation such as data dictionaries, workflow diagrams, and data flow diagrams.
• Safeguard data integrity and security through appropriate controls and ongoing monitoring.
• Optimize pipelines for efficient processing and improved query performance.
• Implement and enforce data security policies, including access controls, encryption, and data masking.
• Design and implement data processing workflows with dbt and Prefect to support data science and machine learning initiatives.
• Develop and maintain data ingestion pipelines to bring external data into the organization’s data environment.
• Identify performance bottlenecks in pipelines and collaborate with infrastructure and operations teams to optimize performance.
• Test and validate data pipelines to verify correct operation and alignment with business requirements.
• Participate in code reviews and help establish engineering best practices.
• Stay informed about emerging data engineering and data science technologies and identify opportunities to adopt them internally.

Requirements

• 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 including window functions, CTEs, and performance tuning on large datasets
• Strong Python for data engineering with 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 such as S3, Glue, and Lambda
• Data quality and observability with dbt plus 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

Technologies

• dbt
• Prefect
• SQL
• Python
• Snowflake
• AWS S3
• AWS Glue
• AWS Lambda
• Terraform
• Git
• Elementary

Benefits

• Medical, dental, and vision benefits
• 15 days PTO per 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