Senior Data Engineer

Wells Fargo

. Develop scalable, secure data pipelines from on-premise systems of record to Google Cloud Platform services .

Posted 10/2/2026full-timeUnited StatesSenior💰 $100,000 - $196,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing scalable and secure data pipelines on Google Cloud Platform, utilizing tools such as BigQuery, Dataflow, and Cloud Composer. Proficient in Python and SQL for building data transformation libraries and implementing predictive AI models.

Highest-signal resume keywords

Data Engineering ExperienceGoogle Cloud Platform (GCP)Python ProgrammingData Pipeline DevelopmentMachine Learning Implementation

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData ModelingPredictive AI ModelsFeature TransformationData Quality AssuranceSQL ProgrammingPython ProgrammingCloud OrchestrationCI/CD IntegrationData Governance

Tools & Technologies

Google Cloud Platform (GCP)BigQueryDataflow/Apache BeamCloud ComposerCloud StorageDataproc/SparkPub/SubGitLiquibaseDAGs/Templates

Industry Keywords

Data EngineeringPublic CloudData Science SolutionsData WorkloadsData IngestionData TransformationData GovernanceMachine Learning AlgorithmsObservabilityStandardized Metrics

Tech Stack

Tools & technologies

AirflowApacheAWSAzureBigQueryCloudGoogle Cloud PlatformOpen SourcePythonSparkSQLVaultGo

About the role

Key responsibilities & impact

Develop scalable, secure data pipelines from on-premise systems of record to Google Cloud Platform services
Leverage and extend roadmaps for reusable ingestion, transformation, quality, and orchestration frameworks and tooling
Enable self-service data consumption and governance through standardized patterns, templates, and sandbox capabilities
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 lineage, dictionary, and high availability
Ensure cost, performance, and reliability of GCP data workloads through partitioning, clustering, storage classes, and autoscaling strategies
Develop transformation libraries in Python, SQL, and Beam
Provide orchestration through Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration
Implement data modeling and semantic layers using dimensional, data vault, or canonical models with 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; provide enablement through workshops and code examples

Requirements

What you’ll need

4+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of 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)
Flexible to provide both application development and production support during off-hours
This role is not eligible for Visa Sponsorship

Benefits

Comp & perks

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
Hybrid schedule (3 days in office, 2 days remote)