Role Title: DBT Developer
Location: Irvine, CA 5 days onsite
Role Summary:
We are seeking a Senior dbt Developer with strong hands-on experience in dbt, Snowflake, and advanced SQL development. The primary focus of this role is to design, build, test, document, deploy, and maintain scalable dbt transformation models on Snowflake that convert raw and source-aligned data into trusted, analytics-ready datasets for reporting, dashboards, and business decision-making.
The ideal candidate will have 4-5 years of experience in data engineering, analytics engineering, BI engineering, or modern data transformation roles, with practical experience using dbt Core and/or dbt Cloud in a production or project-based environment. This role requires strong SQL skills, Snowflake knowledge, good communication skills, and the ability to translate business rules and reporting requirements into reliable dbt models, reusable transformation logic, and governed data marts.
Key Responsibilities:
Design, build, and maintain modular dbt models across staging, intermediate, and marts layers that transform raw data into trusted, analytics-ready datasets.
Develop and optimize dbt incremental models, snapshots, macros, seeds, sources, and reusable packages using dbt Core and/or dbt Cloud.
Write and tune complex SQL transformations in Snowflake using joins, CTEs, window functions, aggregations, conditional logic, and performance optimization techniques.
Optimize Snowflake workloads for query performance, clustering strategy, warehouse sizing, model materialization, processing time, and cost efficiency.
Implement robust data quality and testing frameworks using dbt generic tests, singular tests, custom tests, accepted values, relationships, not-null checks, uniqueness checks, and source freshness checks.
Maintain clear documentation, lineage, dependency mapping, model descriptions, column definitions, source definitions, assumptions, and business logic using dbt docs and exposures.
Manage dbt projects in Git with clean, modular, testable development practices, including branching, pull requests, code reviews, merge controls, and release promotion.
Support CI/CD pipelines for dbt projects using tools such as GitHub Actions, GitLab CI, dbt Cloud jobs, or similar deployment and automation frameworks.
Leverage Snowflake features such as Streams, Tasks, Dynamic Tables, Time Travel, cloning, secure views, and secure data sharing to build reliable ELT workflows.
Create reporting-ready data marts, curated datasets, dimensional models, fact tables, and reusable views that support Tableau dashboards and self-service analytics.
Partner with data engineers, analysts, BI developers, architects, and business stakeholders to translate business requirements into scalable transformation logic.
Troubleshoot data discrepancies, failed dbt runs, source changes, schema changes, model errors, test failures, and performance bottlenecks.
Participate in requirement gathering sessions, technical design discussions, sprint planning, backlog refinement, walkthroughs, and UAT support activities.
Required Qualifications:
Minimum 4+ years of experience in data engineering, analytics engineering, BI engineering, data warehousing, or data transformation roles.
Strong hands-on experience with dbt Core and/or dbt Cloud, including dbt models, macros, tests, snapshots, seeds, sources, packages, documentation, lineage, and project structure.
Strong experience using dbt with Snowflake to build scalable ELT transformation pipelines, curated data models, and analytics-ready datasets.
Strong SQL development skills with experience writing complex transformations, performing data validation, troubleshooting data issues, and analyzing large datasets.
Strong understanding of dbt best practices for modular, testable, well-documented projects.
Hands-on Snowflake experience, including databases, schemas, tables, views, warehouses, roles, access controls, query optimization, and performance considerations.
Strong understanding of data modeling concepts, including star schema, fact and dimension tables, slowly changing dimensions, staging layers, data marts, and semantic/reporting layers.
Experience with data reconciliation and business rule validation.
Ability to translate business requirements, source-to-target mappings, metric definitions, and reporting logic into technical specifications and dbt transformation models.
Good troubleshooting and analytical skills with the ability to identify root causes of data issues, failed transformations, and performance bottlenecks.
Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Analytics, Business Analytics, or a related technical field. Equivalent practical experience may also be considered.
Preferred / Plus Qualifications:
Experience with Tableau, including understanding dashboard requirements, published data sources, extracts, live connections, and reporting-ready data model design.
Experience supporting BI and reporting teams by creating curated datasets, reusable views, semantic layers, and governed data marts.
Experience with advanced dbt capabilities such as dbt Explorer, dbt Semantic Layer, dbt Mesh, exposures, metrics, and cross-project lineage is a plus.
Experience with orchestration and scheduling tools such as Airflow, Dagster, Prefect, Azure Data Factory, Snowflake Tasks, dbt Cloud jobs, or similar platforms.
Experience with CI/CD processes for dbt projects using GitHub Actions, GitLab CI, Azure DevOps, Jenkins, or similar automation tools.
Experience with Python for automation, data validation, testing, metadata extraction, or data engineering support.
Experience with ELT tools such as Fivetran, Airbyte, Matillion, Informatica, Talend, Alteryx, or similar platforms.
Familiarity with cloud ecosystems such as AWS, Azure, or Google Cloud Platform.
Experience with Snowflake performance optimization, warehouse sizing, clustering, query profiling, access control, monitoring, and cost optimization.
Familiarity with Agile delivery, sprint planning, backlog management, Jira/Azure DevOps, and iterative development practices.
Understanding of data governance, metadata management, lineage, access control, PII handling, and enterprise data standards.
Certifications such as dbt Certified Developer, Snowflake certification, Tableau certification, or related cloud/data certifications are a plus.
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