Senior Data Engineer

Wells Fargo

Closes in 4 days Hybrid

Quick summary

Work type: Hybrid
Location: San Francisco, CACharlotte, NC
Salary: $100,000–$196,000 / yr
Posted: 3 days ago
Closes: Jun 19, 2026 (soon)
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $170k

This role $148k

$87k most similar roles pay here $224k

This role pays less than 69% of similar roles. Most pay $135,000–$205,000 — the shaded band above. At the midpoint, this role pays about $148k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About Wells Fargo

Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services

Wells Fargo currently has 87 open roles on FindRole.

Listed pay typically runs $144,009–$224,000 across 46 roles with salary data.

Most-posted roles

View all roles at Wells Fargo

At a glance

TL;DR · Senior Data Engineer

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As a Senior Data Engineer at Wells Fargo’s Global Operations, you will join the AI/ML Data Architecture, Engineering and Enablement team to build scalable data pipelines on Google Cloud Platform (GCP) for enterprise-level machine learning initiatives. Your daily tasks include designing reusable frameworks for data ingestion, transformation, quality checks, and orchestration using Python, SQL, and Apache Beam, while ensuring secure and compliant data solutions. You will collaborate with data scientists to migrate models onto GCP capabilities, implement robust data modeling techniques, and enforce data governance through standardized metrics and monitoring dashboards. The role requires extensive experience in creating analytics solutions on public clouds like GCP, hands-on Python/Go development for data pipelines, and familiarity with machine learning algorithms and model operations technologies such as TensorFlow and PyTorch.

Skills

GoogleCloudPlatform BigQuery Dataflow ApacheBeam Dataproc Spark Pub/Sub CloudStorage Python SQL Go CloudComposer Airflow CI/CD Git Liquibase CloudLogging CloudMonitoring Jupyter TensorFlow XGBoost Scikit-learn BigTable CloudWorkflows DAGs DimensionalModeling DataVault SemanticLayer CloudBilling Partitioning Clustering StorageClasses AutoscalingStrategies

What you'll do

Develop scalable, secure data pipelines from on-premise systems to Google Cloud Platform services.
Extend capability roadmaps for reusable frameworks and tooling in GCP actively developed by the organization.
Enable self-service data consumption and governance through standardized patterns and templates.
Create standardized feature transformation pipelines with strong lineage and high availability for models.
Ensure cost, performance, and reliability of GCP data workloads using appropriate strategies.

What we're looking for

4+ years of Data Engineering experience in Public Cloud (GCP, AWS, Azure)
Extensive hands-on experience with Python/Go for building data pipelines and automation tooling
Proficiency in GCP orchestration tools (Composer/Airflow/Dataflow/Beam) and CI/CD practices
Solid background in developing predictive AI models using machine learning algorithms
Expertise in creating scalable, secure data pipelines from on-premise to Google Cloud Platform services

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