Wells Fargo
Wells Fargo
Wells Fargo — банк ісі және онымен байланысты қаржылық өнімдер саласында жұмыс істейтін көпұлтты қаржылық қызметтер компаниясы. Компанияның жұмысқа қабылдау бағыттары мансабын енді бастап келе жатқан мамандарға, тәжірибелі сарапшыларға және көшбасшыларға арналған мүмкіндіктерді қамтиды. Бұл ретте ынтымақтастыққа, инновацияларға және инклюзивті жұмыс ортасына басымдық беріледі. Сондай-ақ компания қызметкерлерінің кең ауқымындағы мансаптық өсуге қолдау көрсетуге арналған даму бағдарламаларын ұсынады.

Senior Data Engineer, GCP AI/ML (Hybrid)

Build secure Google Cloud data pipelines and reusable AI/ML infrastructure at Wells Fargo. Support governed analytics, model operations, and enterprise-scale data capabilities.

Сипаттама

  • Build scalable, secure pipelines from on-premises systems of record to Google Cloud services
  • Extend reusable frameworks for data ingestion, transformation, quality, and orchestration
  • Enable governed, self-service data access through standardized patterns, templates, and sandbox environments
  • Support model training, validation, and monitoring with BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage
  • Develop standardized feature pipelines and a highly available feature store with lineage and data definitions
  • Optimize GCP workload cost, performance, and reliability through partitioning, clustering, storage classes, and autoscaling
  • Create transformation libraries with Python, SQL, and Beam
  • Orchestrate workloads through Cloud Composer or Cloud Workflows using reusable DAGs, templates, and CI/CD integration
  • Implement dimensional, data vault, or canonical data models and semantic layers with BigQuery or comparable tools
  • Establish data quality, lineage, and observability through standardized metrics, validation rules, and monitoring dashboards
  • Collaborate with data scientists and domain solution teams to migrate existing models to GCP
  • Document patterns, runbooks, and best practices while enabling teams through workshops and code examples

Талаптар

  • At least four years of data engineering experience, or equivalent experience, training, military service, or education
  • At least four years of experience developing analytics or data science solutions in a public cloud such as GCP, AWS, or Azure
  • At least four years of hands-on Python and/or Go experience building data pipelines, libraries, and automation tools
  • At least four years working with GCP or comparable open-source orchestration tools such as Composer, Airflow, Dataflow, or Beam, plus Git, Liquibase, and CI/CD for data workloads
  • At least two years of hands-on experience developing and implementing predictive machine learning models, including regression, classification, or forecasting
  • Availability to provide application development and production support outside standard working hours
  • This position is not eligible for visa sponsorship

Артықшылықтар

  • Health benefits
  • 401(k) plan
  • Paid time off
  • Disability benefits
  • Life, critical illness, and accident insurance
  • Parental leave
  • Critical caregiving leave
  • Discounts and savings programs
  • Commuter benefits
  • Tuition reimbursement
  • Scholarships for dependent children
  • Adoption reimbursement
  • Hybrid schedule with three days in the office and two days working remotely

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