Data Engineer

Responsibilities

• 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

Qualifications

• 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

Benefits & Perks

• 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