Lead Data Engineer

Lead Data Engineer role within Wells Fargo’s COO Technology organization, focused on designing, building, and operating cloud-native, reusable data capabilities on Google Cloud. This hybrid position in Irving, TX supports enterprise analytics and AI by scaling secure data platforms, patterns, and platform services that multiple product and domain teams can adopt.

You will work on managed GCP data services and reusable frameworks, with a strong emphasis on governance-by-design, self-service data consumption, orchestration, and operational excellence. Wells Fargo also expects flexibility to cover application development and production support during off-hours, alongside ownership, transparency, and continuous learning.

Responsibilities

• Design and implement scalable, secure data platforms on Google Cloud using managed services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Composer.
• Build reusable frameworks and tooling for ingestion, transformation, quality, and orchestration that can be used by multiple product and domain teams.
• Enable self-service data by standardizing patterns, templates, and platform capabilities instead of creating one-off pipelines.
• Design logical and physical architectures leveraging BigQuery, Dataflow/Apache Beam, Dataproc/Spark, Pub/Sub, and Cloud Storage.
• Define standardized batch and streaming ingestion, transformation, and serving blueprints.
• Optimize cost, performance, and reliability through partitioning, clustering, storage classes, and autoscaling strategies.
• Develop opinionated ingestion frameworks, including config-driven pipelines, connectors, schema handling, and error handling built on top of Dataflow, Dataproc, or Composer.
• Create shared transformation libraries in Python/SQL/Beam, such as common SCD patterns, data quality checks, and masking/tokenization routines.
• Provide orchestration capabilities using Cloud Composer or Cloud Workflows with reusable DAGs/templates and CI/CD integration.
• Implement robust data modeling (dimensional, data vault, or canonical) and semantic layers in BigQuery and related tools.
• Enforce data quality, lineage, and observability with standardized metrics, validation rules, and monitoring dashboards.
• Apply security and governance controls including IAM, VPC-SC, CMEK, and row/column-level security with policy-driven access patterns.
• Partner with domain data engineers, analytics, and ML teams to onboard use cases to platform services and frameworks.
• Document patterns, runbooks, and best practices, and provide enablement through workshops and code examples.
• Contribute to the platform roadmap, including tool selection and evaluation of new GCP services and open-source components.

Requirements

• 5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of work experience, training, military experience, or education.
• 5+ years of data management experience in Public Cloud (GCP, AWS, or Azure).
• 5+ years hands-on experience of Python or Java, plus Spark SQL for building pipelines, libraries, and automation tooling.
• 5+ years with orchestration tools ( Cloud Composer/Airflow ) and CI/CD ( Cloud Build, Git-based workflows ) for data workloads.

Additional Information

• Hybrid schedule: 3 days in office, 2 days remote.
• Work coverage: flexible to provide application development and production support during off-hours.
• Visa sponsorship: this role is not eligible for Visa Sponsorship.
• Locations: 300 S Brevard St., Charlotte, NC 28202 and 401 Las Colinas Blvd W Bldg A, Irving, TX 75039.
• Posting end date: 19 Oct 2026 (job posting may come down early due to volume of applicants).

Technologies

• Google Cloud Platform, BigQuery, Dataflow, Apache Beam, Dataproc, Spark, Pub/Sub, Cloud Storage, Composer, Cloud Workflows
• Python, Java, Spark SQL, SQL
• Airflow, Cloud Build, Git-based workflows, IAM, VPC-SC, CMEK

Desired Qualifications

• Experience with logging and monitoring stacks (Cloud Logging, Cloud Monitoring, error reporting, metrics dashboards).
• Experience with automated testing, data quality checks, and monitoring for pipelines and platform services.
• Knowledge of cloud architecture principles including networking, security, IAM, reliability, and cost management.
• Experience with core GCP data services: BigQuery, Dataflow/Apache Beam, Dataproc, Pub/Sub.
• Experience with Agile transformations and technology roadmaps.
• Experience working with onshore and offshore teams.

Disability & Compliance Notes

• To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.
• Wells Fargo maintains a drug free workplace.
• Third-party recordings are prohibited unless authorized by Wells Fargo.
• Wells Fargo requires you to directly represent your own experiences during recruiting and hiring.