Senior Data Engineer

Join the AI/ML Data Architecture, Engineering and Enablement team within Wells Fargo’s Global Operations. We build cross-cutting data capabilities that empower data scientists from experimentation through monitoring. As a Senior Data Engineer, you’ll design, build, and operate reusable GCP-based data frameworks that enable secure, self-service, and governed machine-learning solutions at enterprise scale.

Responsibilities

• Develop scalable, secure data pipelines from on-premise systems of record to Google Cloud Platform services (BigQuery, BigTable, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Composer).
• Leverage and extend capability roadmaps for reusable frameworks and tooling (ingestion, transformation, quality, orchestration) actively being developed by the larger organization.
• Enable self-service data consumption and governance by standardizing patterns, templates, and sandbox capabilities rather than one-off pipelines.
• Support use cases for training, validation, and monitoring leveraging 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, and high availability for models.
• Ensure appropriate cost, performance, and reliability of GCP data workloads (partitioning, clustering, storage classes, autoscaling strategies).
• Develop transformation libraries in Python/SQL/Beam (e.g., common SCD patterns, data quality checks, masking/tokenization routines).
• Provide orchestration capabilities via Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration.
• Implement robust data modeling (dimensional, data vault, or canonical models) and semantic layer implementations with BigQuery or similar tools.
• Enforce data quality, lineage, and observability using 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, and provide enablement through workshops and code examples.

Requirements

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

Qualifications

• Experience with logging/monitoring stacks (Cloud Logging, Cloud Monitoring, error reporting, 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 such as clustering, classification, logistic regression, natural language processing, neural networks, ensembling, computer vision, time-series analysis.
• Experience with data optimization and availability in generative AI solutions such as RAGs, knowledge graphs, MCPs, vectors, prompt validation, and tuning environments.

Job Expectations

• Flexible to provide both application development and production support during off-hours.
• Hybrid schedule: 3 days in office, 2 days remote.
• Work transparently: deal honestly, directly, and transparently.
• Take ownership: welcome accountability and find joy in providing answers.
• Learn more: regularly self-educate and improve your skill set.
• Embrace change: remain motivated and flexible as technology evolves.

Locations: 333 Market St, San Francisco, California 94105 and 1525 W W T Harris Blvd., Charlotte, North Carolina 28262.

Pay

$100,000.00 - $196,000.00 base pay range. Pay may vary depending on factors including demonstrated prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.

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