dbt (Data Build Tool) Developer
Job Description
About the Role
We are looking for a dbt (Data Build Tool) Developer to design, optimize, and maintain data systems built on dbt Core, dbt Cloud, Jinja Templating. This role combines technical depth in dbt (Data Build Tool) with the ability to understand business context — you'll work with analysts, engineers, and stakeholders to ensure data is reliable, accessible, and useful. The ideal candidate has hands-on experience with Snowflake and BigQuery, can diagnose complex query performance issues, and understands both OLTP and OLAP patterns. You'll own data pipeline reliability, query performance, and schema evolution for systems handling millions of records.
Key Responsibilities
- Own dbt Core implementation and optimization — configuration, customization, and ongoing enhancement based on business needs
- Manage dbt Cloud workflows including setup, user training, and continuous improvement of processes
- Implement and maintain Jinja Templating ensuring seamless integration with existing systems and workflows
- Design and maintain dbt (Data Build Tool) schemas optimized for both operational and analytical workloads
- Write and optimize complex queries, stored procedures, and data transformation pipelines
- Monitor dbt (Data Build Tool) performance — query execution plans, resource utilization, and capacity planning
- Build automated ETL/ELT pipelines for data integration from multiple source systems
- Create dashboards and reporting solutions that enable data-driven decision making
- Implement data quality checks, validation rules, and monitoring for data pipeline reliability
- Plan and execute database migrations with zero-downtime cutover strategies
Must-Have Qualifications
- Hands-on experience with dbt Core — configuration, customization, and troubleshooting in production environments
- Proficiency with Snowflake as part of the dbt (Data Build Tool) development/operations workflow
- 3+ years of hands-on dbt (Data Build Tool) experience in production environments
- Strong SQL skills — complex queries, window functions, CTEs, and query optimization
- Experience with data modeling — star schemas, normalization, and denormalization trade-offs
- Understanding of ETL/ELT pipeline design and data quality management
- Ability to communicate data insights to both technical and non-technical stakeholders
Nice-to-Have Skills
- dbt Certified Analytics Engineer certification or equivalent validated credential
- Experience with advanced dbt (Data Build Tool) features: dbt Cloud, Jinja Templating, Data Testing
- Familiarity with the broader dbt (Data Build Tool) ecosystem including BigQuery and Databricks
- Experience with real-time streaming systems (Kafka, Kinesis, or Flink)
- Knowledge of data governance frameworks and data catalog tools
Interview Tips
Technical Coding Exercise
Give a small, realistic dbt (Data Build Tool) coding challenge that tests fundamentals — clean code, edge case handling, and test writing. Time-box to 45-60 minutes.
Architecture Whiteboard
Present a system design problem relevant to dbt (Data Build Tool). Evaluate their approach to scalability, data modeling, and trade-off discussions.
Code Review Simulation
Show a dbt (Data Build Tool) pull request with both good patterns and subtle issues. Assess what they catch, how they communicate feedback, and what they prioritize.
Past Project Deep-Dive
Have them walk through their most challenging dbt (Data Build Tool) project. Ask probing questions about architecture decisions, obstacles, and what they learned.
Typical Team Structure
Team Size
2-5 dbt (Data Build Tool) developers
Reports To
Engineering Manager, Tech Lead, or CTO
Collaborates With
Product Management, QA/Testing, DevOps, Design
Skip the JD — Get Matched Instead
Tell us your dbt (Data Build Tool) requirements and we'll send pre-vetted profiles with video intros in 24-48 hours.
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