Cloud Data Engineer

Job Description

Job Description

Responsibilities

Artificial Intelligence; Advanced Technology; The very best in patient care. With decades of expertise, RadNet is Leading Radiology Forward . With dynamic cross-training and advancement opportunities in a team-focused environment, the core of RadNet’s success is its people with the commitment to a better healthcare experience. When you join RadNet as a Cloud Data Engineer , you will be joining a dedicated team of professionals who deliver quality, value, and access in the 21st century and align all stakeholders- patients, providers, payors, and regulators to achieve the best clinical outcomes.

You Will :

• Own end-to-end development of cloud ELT pipelines — from CDC / API ingestion (Airbyte) and batch loads (Cloud Build / Composer) into BigQuery landing tables to dbt transformations that publish curated Silver / Gold datasets.
• Design and document Medallion-style models (Bronze → Silver → Gold) in dbt with clear naming, sources, exposures, and owners; maintain dbt project structure, packages, and environments.
• Implement data quality with dbt tests (generic / custom), freshness checks, and documentation (dbt docs); publish artifacts to the Analytics Hub / catalog for discoverability.
• Optimize BigQuery for dbt : partitioning, clustering, materializations (incremental / merge), cost controls (slots / quotas), job monitoring, and query performance tuning.
• Support streaming use cases by landing real time data via Pub / Sub with BigQuery subscriptions (or Dataflow / Beam where required) and shaping near real time models with dbt incremental strategies.
• Build orchestration and CI / CD for dbt using dbt Cloud or dbt Core (Cloud Build / Composer), with code review, automated tests, and artifact promotion across Dev / Test / Prod.
• Partner with BI and AI / ML teams to expose trusted datasets and features; publish contract backed schemas and semantic conventions aligned to enterprise KPIs.
• Migrate and reconcile legacy on prem pipelines (e.g., SQL Server CDC) into GCP; validate row level fidelity and handle late arriving and schema evolution scenarios.
• Implement security, privacy, and governance (IAM, CMEK, BQ row / object level security, HIPAA); contribute to auditable data lineage (dbt exposures + warehouse lineage).
• Establish monitoring / alerting for pipeline reliability (Cloud Monitoring / Logging), with SLAs / SLOs, retries / backfills, and incident runbooks; participate in on call as needed.

If You Are :

To Ensure Success in This Role, You Must Have :

We Offer :