Design, build, and optimize data models and transformations in BigQuery using SQL , CTEs , window functions , and incremental logic .
Develop modular, reusable pipelines using Dataform or dbt , ensuring proper documentation, dependencies, and version control.
Collaborate with data architects, analysts, and business teams to define and maintain governed data layers .
Maintain and validate Looker dashboards to ensure parity between legacy (Roadnet) and modernized data sources.
Participate in the design of data architecture and lineage , ensuring consistency, scalability, and performance optimization.
Partner with governance and infrastructure teams to establish best practices for data quality, model ownership, and CI / CD workflows.
Automate and operationalize data tasks using Python , Cloud Functions , or Terraform (as applicable).
Ideal Candidate Profile
5–9 years of experience in data engineering or analytics engineering roles.
Proven experience in BigQuery , dbt / Dataform , and Looker within the GCP environment .
Strong understanding of data architecture , lineage , and governed data modeling .
Hands-on experience with SQL performance optimization and data quality management .
Excellent collaboration and communication skills to work with cross-functional teams.
Exposure to transportation, logistics, or routing analytics is a plus.
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