What are the responsibilities and job description for the Lead Cloud Data Platform Engineer position at wellsfargo?
Title: Lead Cloud Data Platform Engineer
Locations: Phoenix, AZ
Alternate Locations: Dallas, TX or Minneapolis, MN
Duration: 12 months
Work Engagement: W2
Work Schedule: 3 days in office/2 days remote
Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits
Summary:
In this contingent resource assignment, you may: Consult on complex initiatives with broad impact and large-scale planning for Software Engineering. Review and analyze complex multi-faceted, larger scale or longer-term Software Engineering challenges that require in-depth evaluation of multiple factors including intangibles or unprecedented factors. Contribute to the resolution of complex and multi-faceted situations requiring solid understanding of the function, policies, procedures, and compliance requirements that meet deliverables. Strategically collaborate and consult with client personnel. Required Qualifications: 5 years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
We are currently seeking a Lead Cloud Data Platform Engineer to apply deep technical skills to create data products, develop AI-based automation tools, and build a world-class cloud analytics capability for Wells Fargo’s Cyber Security Data Ecosystem on a Hybrid cloud. The successful candidate will continually innovate and pioneer the use of new technologies, and drive adoption of these amongst a team of talented data engineers. You will be an integral part of our migration from our on-premises systems to the Google Azure cloud. You will be a vital member of an agile team helping to lead the design and hands-on implementation of modern data processing capabilities. This is a visible role that allows you to share your knowledge and skills with other developers and product teams in a collaborative environment.
In this role you will:
Implement and operationalize modern AI-enabled data capabilities on Google Cloud to ingest, transform, and distribute data for a variety of big data apps
Leverage AI/Agentic frameworks to automate data management, governance, and data consumption capabilities - data pipelines, data quality, metadata, data compliance, etc.
Work within a matrix org. with principal engineers, product managers, and data engineers to roadmap, plan, and deliver key data capabilities based on priority
Qualifications:
Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.
6-7 months AI experience
GCP experience (min 2 yrs experience)
Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
5 years of experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
3 years of experience with Data Lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, Big Query, Data Proc, Cloud Composer
Hands-on experience developing data flows using Kafka, Flink, and Spark streaming