Senior Data Engineer

Wells Fargo is seeking a Senior Data Engineer to design, build, and operate reusable data capabilities on Google Cloud Platform to support enterprise machine learning and AI.

Responsibilities

• Develop scalable, secure data pipelines from on-premise systems of record to GCP services including BigQuery, BigTable, Dataflow, Dataproc, Pub/Sub, and Cloud Storage
• Leverage and extend enterprise capability roadmaps for reusable frameworks and tooling across ingestion, transformation, quality, and orchestration
• Enable self-service data consumption and governance by standardizing patterns, templates, and sandbox capabilities instead of building one-off pipelines
• Support training, validation, and monitoring use cases using BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage
• Create standardized feature transformation pipelines and a common feature store with strong lineage, dictionary capabilities, and high availability for models
• Optimize cost, performance, and reliability for GCP data workloads using partitioning, clustering, storage classes, and autoscaling strategies
• Develop transformation libraries in Python/SQL/Beam including common SCD patterns, data quality checks, and masking or tokenization routines
• Provide orchestration using Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration
• Implement robust data modeling approaches (dimensional, data vault, or canonical models) and semantic layer implementations using BigQuery or similar tools
• Enforce data quality, lineage, and observability through standardized metrics, validation rules, and monitoring dashboards
• Partner with data scientists and domain solution teams to migrate existing models onto GCP capabilities
• Document patterns, runbooks, and best practices; deliver enablement via workshops and code examples
• Be flexible to provide application development and production support during off-hours

Requirements

• 4+ years of data engineering experience, or equivalent demonstrated through one or a combination of work experience, training, military experience, or education
• 4+ years creating analytics or data science solutions in public cloud (GCP, AWS, or Azure)
• 4+ years hands-on experience building data pipelines, libraries, and automation tooling using Python and/or Go
• 4+ years working with GCP or equivalent open source orchestration tools (Composer/Airflow/Dataflow/Beam) and CI/CD (including Git and Liquibase) for data workloads
• 2+ years hands-on experience building and implementing predictive AI models using machine learning algorithms (regression, classification, forecasting)

Technologies

• Google Cloud Platform (GCP), BigQuery, BigTable
• Dataflow, Dataproc, Pub/Sub, Cloud Storage
• Composer, Apache Beam, Spark, Cloud Workflows
• Python, SQL, Beam, Go
• Cloud Composer, Cloud Logging, Cloud Monitoring
• Vertex, Bedrock, SageMaker, Jupyter, Hugging Face
• TensorFlow, XGBoost, Anaconda, MLFlow, PyTorch, Scikit-learn
• Git, Liquibase

Benefits

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement

Desired Qualifications

• Experience with logging and monitoring stacks including Cloud Logging, Cloud Monitoring, error reporting, and metrics dashboards
• Experience with automated testing, data quality checks, monitoring for pipelines, and model governance such as drift, bias, and anomaly detection
• Experience with model development and operations technologies such as Vertex, Bedrock, SageMaker, Jupyter, Hugging Face, TensorFlow, XGBoost, Anaconda, MLFlow, PyTorch, Scikit-learn
• Experience with modeling techniques including clustering, classification, logistic regression, natural language processing, neural networks, ensembling, computer vision, and time-series analysis
• Experience with data optimization and availability in generative AI solutions including RAGs, knowledge graphs, MCPs, vectors, prompt validation, and tuning environments

Job Expectations

• Hybrid schedule (3 days in office, 2 days remote)
• Not eligible for Visa Sponsorship
• Work transparently with honest, direct, and transparent communication
• Take ownership by embracing accountability and providing answers
• Regularly self-educate and improve skill set
• Embrace change by adapting and remaining flexible as technology evolves

Additional Information

• Locations: 333 Market St, San Francisco, California 94105; 1525 W W T Harris Blvd., CHARLOTTE, North Carolina 28262
• Pay range: $100,000.00 - $196,000.00 per year
• Posting end date: 8 Oct 2026 (job posting may come down early due to volume of applicants)
• Applicants with disabilities: request a medical accommodation via Disability Inclusion at Wells Fargo
• Drug and alcohol policy: Wells Fargo maintains a drug-free workplace
• Recruitment and hiring requirements: Third-party recordings are prohibited unless authorized by Wells Fargo; candidates must directly represent their own experiences during recruiting and hiring