What are the responsibilities and job description for the Senior AI Data Engineer position at wellsfargo?
Description
Title:Senior AI Data Engineer
Location: Phoenix, AZ
Alternative Location: Chandler, AZ - Charlotte, NC - Las Colinas, TX
Duration: 12 months
Work Engagement: W2
Work Schedule: Hybrid 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 or participate in moderately complex initiatives and deliverables within Software Engineering and contribute to large-scale planning related to Software Engineering deliverables. Review and analyze moderately complex Software Engineering challenges that require an in-depth evaluation of variable factors. Contribute to the resolution of moderately complex issues and consult with others to meet Software Engineering deliverables while leveraging solid understanding of the function, policies, procedures, and compliance requirements. Collaborate with client personnel in Software Engineering. Required Qualifications: Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education.
Key Responsibilities:
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.
Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
Experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
Dxperience with Data lakehouse architecture and design, including hands-on experience with Python, pySpark, Kafka, Airflow, Google Cloud Storage, BigQuery, Data Proc, Cloud Composer
Hands-on experience developing data flows using Kafka, Flink, and Spark streaming
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Key Requirements:
· Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship.
GCP
AI exposure - 6 months to a year
Demonstrable skills (recent) using AI tools such as LangChain, LangGraph/ADK, agentic frameworks, RAG, GraphRAG, and using MCP to build agent-based data capabilities
Experience in data engineering including hands-on experience working with Cloud data solutions: creating/supporting Spark based ingestion and processing
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