Data Engineer II
Summary
Data Engineer II at Dave builds and owns production data pipelines end to end—ingestion, transformation, validation, monitoring, and support—using Snowflake, dbt, Airflow/Cloud Composer, Python or Java, SQL, and cloud services, with a focus on data quality, performance, and AI-assisted engineering workflows.
You build and improve reliable data pipelines that ingest, transform, validate, and deliver data. You own projects through implementation, testing, deployment, monitoring, troubleshooting, and ongoing production support. You work with Snowflake, dbt, Airflow, APIs, files, and cloud services while improving reliability, performance, scalability, and cost. You also contribute to schema design, data modeling, documentation, data quality, query optimization, alerting, backfills, and AI-assisted engineering workflows.
Responsibilities
- Build, maintain, and improve reliable data pipelines.
- Own data engineering projects through implementation, testing, deployment, monitoring, troubleshooting, and production support.
- Work with Snowflake, dbt, Airflow or Cloud Composer, APIs, files, and cloud services.
- Design schemas and data models and improve data quality and query performance.
- Improve ingestion, orchestration, validation, retries, backfills, monitoring, and alerting.
- Use AI-assisted engineering tools for development, debugging, documentation, and analysis.
Requirements
- 2+ years of software or data engineering experience supporting production data systems.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience.
- Strong programming skills in Python, Java, or another general-purpose language.
- Strong SQL skills.
- Experience building or maintaining ETL or ELT pipelines with dbt, Fivetran, or similar tools.
- Experience with Snowflake, BigQuery, or Redshift and Airflow or Cloud Composer.
- Understanding of data modeling, data quality, relational data, query optimization, and performance optimization.
- Experience with version control, testing, code reviews, and CI/CD.
- Ability to troubleshoot production systems methodically and communicate effectively with technical and business partners.
Benefits
- Flexible hours
- Home office stipend
- Premium medical, dental, and vision insurance
- Paid parental and caregiver leave
- 401(k) savings plan with matching contributions
- Financial advisor and financial wellness support
- Flexible paid time off
- Generous company holidays including Juneteenth and Winter Break
- All-company in-person events once or twice a year and virtual events
What they ask for
Required
- 2+ years of software or data engineering experience supporting production data systems
- Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field, or equivalent practical experience
- Strong programming skills in Python, Java, or another general-purpose language
- Strong SQL skills
- Experience building or maintaining ETL/ELT pipelines with dbt, Fivetran, or similar tools
- Experience with Snowflake, BigQuery, or Redshift and Airflow or Cloud Composer
- Understanding of data modeling, data quality, relational data, query optimization, and performance optimization
- Experience with version control, testing, code reviews, and CI/CD
- Ability to troubleshoot production systems methodically and communicate effectively with technical and business partners