Developer Enablement: Create high-quality developer documentation, reference implementations, and tutorials to drive community adoption of BigQuery Graphs and Measure. CI/CD & Automation: Develop reference CI/CD pipelines (e.g., GitHub Actions, GitLab CI) that parse, validate, and deploy BigQuery graphs defined in declarative YAML formats.
Numbers & Facts
Location
NULL, AK (Remote)
Description
Role : Software Developer
Locations: Remote
Rate: On C2C
All Visa
Responsibilities:
Semantic Modeling Research: Research and compare the semantic and metric modeling capabilities of Looker, dbt (MetricFlow), Snowflake, and Databricks. Deliver a prioritized backlog of BQ measure features with a repository of real-world samples and direct source links.
dbt Package Development: Build, publish, and maintain an open-source dbt package library to introduce BigQuery graph as a dbt materialization.
CI/CD & Automation: Develop reference CI/CD pipelines (e.g., GitHub Actions, GitLab CI) that parse, validate, and deploy BigQuery graphs defined in declarative YAML formats.
Developer Enablement: Create high-quality developer documentation, reference implementations, and tutorials to drive community adoption of BigQuery Graphs and Measure
Qualifications:
Bachelor's degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience. At least 4 years of software development experience, with a strong proficiency in Python packaging, testing (pytest), and validation.
Extensive hands-on experience with dbt (dbt-core), specifically in building custom materializations, Jinja macros, and package integrations.
Strong SQL proficiency (including complex aggregations, window functions, and schema modeling) and deep production experience with Google Cloud BigQuery.
Analytical mindset with the ability to research complex technical specifications and translate findings into structured backlogs and architectural designs
Desired Skills:
Hands-on experience modeling with metric/semantic layers (e.g., LookML, dbt MetricFlow, Cube, or Snowflake/Databricks metric features).
Experience with Property Graphs queries ISO GQL, SQL or graph database engines.
Experience with CI/CD tools and declarative schema compilers (e.g., YAML/JSON validation via Pydantic).
Active participation or maintainer status in open-source data communities.