Cloud Data Engineer

Responsibilities

Artificial Intelligence;
Advanced Technology;
The very best in patient care. With decades of expertise, Rad Net is Leading Radiology Forward. With dynamic cross-training and advancement opportunities in a team-focused environment, the core of Rad Net’s success is its people with the commitment to a better healthcare experience. When you join Rad Net 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.

• Own end-to-end development of cloud ELT pipelines — from CDC/API ingestion (Airbyte) and batch loads (Cloud Build/Composer) into Big Query 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 Big Query 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 Big Query 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.

• Passionate about patient care and exercise sound judgement and an ability to remain professional in all situations.
• You demonstrate effective and professional communication, interpersonal skills and respect with patients, guests & colleagues.
• You have a structured work-approach, understand complex problems and you are able to prioritize work in a fast-paced environment.

• 5+ years in data engineering with GCP experience.
• Strong Python and SQL.
• Hands‑on with Big Query, Dataflow, Pub/Sub, and Dataproc.
• Experience with dbt/Airflow/Composer for orchestration.
• Experience integrating APIs and SaaS sources using Airbyte.
• Knowledge of data formats (Parquet, Avro, JSON, Delta Lake).
• Experience with Mongo
  
  DB Atlas or Neo4j AuraDB preferred.
• Familiarity with vector search or graph analytics preferred.
• Healthcare data experience (HL7, FHIR) preferred.

• Comprehensive Medical, Dental and Vision coverages.
• Health Savings Accounts with employer funding.
• Wellness dollars
• 401(k) Employer Match
• Free services at any of our imaging centers for you and your immediate family.