Lead Data Engineer GCP Platform Services & Frameworks

About this role:

The COO Technology group delivers technology solutions for the Chief Operating Office supporting operations control executives strategic execution business continuity resiliency data services regulatory relations customer experience enterprise shared services supply chain management and corporate properties. Our mission is to modernize and optimize technology platforms for these critical functions.

Within COO Technology we are seeking a Lead Data Engineer who will be responsible for designing GCPbased data pipeline development semantic layers and reporting capabilities that support frontoffice middleoffice and finance functions. The role will ensure data is accurate reconciled wellgoverned and consumable via standardized and selfservice analytics and dashboards as well as consumable APIs for downstream systems.

In this role you will:

• Lead the design and implementation of scalable secure data platforms on Google Cloud using managed services (BigQuery Dataflow Dataproc Pub/Sub Cloud Storage Composer)
• Build reusable frameworks and tooling (ingestion transformation quality orchestration) that can be adopted by multiple product and domain teams
• Develop shared 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
• Optimize cost performance and reliability of GCP data workloads (partitioning clustering storage classes autoscaling strategies)
• Build opinionated data ingestion frameworks (e.g. configdriven pipelines connectors schema handling error handling) on top of Dataflow Dataproc or Composer
• Implement robust data modeling (dimensional data vault or canonical models) and semantic layers in BigQuery and related tools
• Enforce data quality lineage and observability using standardized metrics validation rules and monitoring dashboards
• Partner with domain data engineers analytics and ML teams to onboard use cases onto platform services and frameworks
• Document patterns runbooks and best practices and provide enablement through workshops and code examples
• Contribute to platform roadmap tool selection and evaluation of new GCP services and opensource components

Required Qualifications:

• 5 years of Data Engineering experience or equivalent demonstrated through one or a combination of the following: work experience training military experience education
• 4 years with orchestration tools (Cloud Composer/Airflow) and CI/CD (Cloud Build Gitbased workflows) for data workloads
• 4 Python and Spark for building data pipelines libraries and automation tooling
• 4 years of advanced SQL and data modeling for analytics and warehousing; experience with ETL/ELT design patterns
• 4 years experience with automated testing data quality checks and monitoring for pipelines and platform services
• 4 years experience with logging/monitoring stacks (Cloud Logging Cloud Monitoring error reporting metrics dashboards
• 3 years of experience with core GCP data services: BigQuery Dataflow/Apache Beam Dataproc Pub/Sub

Desired Qualifications:

• Bachelors degree in computer science Engineering or related field or equivalent
• Experience with knowledge graphs and semantic search
• Excellent communication and presentation skills across technical audiences
• Advanced Data Modeling skills including data modeling in tabular and MPP models design composite models and performance optimization of large complex datasets
• Strong SQL expertise and handson experience with Starburst and/or Trino including connector configuration query optimization and secure data federation across GCP data stores
• Collaborative mindset with a focus on partnering across business finance risk and technology teams to deliver highquality reconciled data APIs and reporting outcomes
• Experience in large financial services organizations (100k employees)
• Experience with Agile transformations and technology roadmaps
• Experience working with onshore and offshore teams

Job Expectations:

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

Pay Range

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance skills experience or work location. Employees may also be eligible for incentive opportunities.

Posting End Date:

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability status as a protected veteran or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit Market Financial Crimes Operational Regulatory Compliance) which includes effectively following and adhering to applicable Wells Fargo policies and procedures appropriately fulfilling risk and compliance obligations timely and effective escalation and remediation of issues and making sound risk decisions. There is emphasis on proactive monitoring governance risk identification and escalation as well as making sound risk decisions commensurate with the business units risk appetite and all risk and compliance program requirements.

Applicants with Disabilities

To request a medical accommodation during the application or interview process visitDisability Inclusion at Wells Fargo.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.

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a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.