Data Engineer
Job Description
Join Crumbl's data team at the Provo headquarters to help turn raw data into actionable insights. This on site Data Engineer role focuses on building and maintaining scalable data pipelines that power data driven decisions across the organization, using dbt and Prefect to orchestrate data workflows. You will partner with data scientists, analysts, and other stakeholders to ensure data quality and accessibility.
Responsibilities
- Design, build, and maintain scalable and reliable data pipelines through ELT and ETL.
- Collaborate with data scientists, analysts, and stakeholders to capture data requirements and uphold data quality.
- Develop and maintain documentation, including data dictionaries, workflow diagrams, and data flow diagrams.
- Safeguard data integrity and security by implementing appropriate controls and monitoring.
- Tune data pipelines to optimize processing efficiency 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 pipelines and collaborate with infrastructure and operations teams to optimize system performance.
- Test and validate data pipelines to ensure they are functioning correctly and meeting business requirements.
- Participate in code reviews and contribute to the development of data engineering best practices.
- Stay current with emerging technologies and trends in data engineering and data science, identifying opportunities to leverage them within the organization.
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 with window functions, CTEs, and performance tuning on large datasets.
- Strong Python for data engineering, emphasizing modular, testable pipeline code.
- Hands-on dbt experience, including models, tests, macros, and incremental materializations.
- Production Snowflake experience: schema design, performance tuning, and warehouse/cost optimization.
- AWS data services experience (S3, Glue, 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 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
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