AI Data Analytics Architect / Senior AI Data Analytics & Automation Lead - Charlotte, NC (Hybrid) | W2 Contract

Job ID: 178212

Position: AI Data Analytics Architect / Senior AI Data Analytics & Automation Lead

Client: Wells Fargo

Location: Charlotte, NC (Hybrid/Onsite)

Work Location: 11625 N Community House Rd., Charlotte, NC

Duration: Through January 30, 2027 (Long-Term Contract)

Employment Type: W2 Only

Pay Rate: Up to $69.50/hr W2 + Benefits

Job Summary

We are seeking a Senior AI Data Analytics & Automation Lead to help drive enterprise analytics, intelligent automation, and AI-powered business solutions. This role is ideal for someone who combines expertise in Power BI, Python, SQL, Data Engineering, and Generative AI to build scalable reporting platforms, automate business processes, and develop AI-driven productivity solutions.

The ideal candidate is passionate about data, automation, modern AI technologies, and partnering with business leaders to deliver impactful enterprise solutions.

Key Responsibilities

Data Analytics & Business Intelligence

• Design, develop, and optimize executive dashboards using Power BI.

• Build scalable KPI, operational, and executive reporting solutions.

• Create advanced data models, DAX calculations, and Power Query transformations.

• Translate complex business data into actionable insights and visualizations.

• Develop advanced Excel-based reporting and analytical models.

Data Engineering & Automation

• Build Python-based automation for reporting, reconciliation, and workflow optimization.

• Develop ETL/ELT pipelines integrating enterprise data sources.

• Automate recurring reporting processes to improve efficiency and data quality.

• Implement data governance, monitoring, and quality controls.

AI & Intelligent Automation

• Design and implement Generative AI and Agentic AI solutions.

• Build AI-powered assistants, workflow automation, and decision-support tools.

• Develop solutions using:

  • Large Language Models (LLMs)

  • Prompt Engineering

  • Retrieval-Augmented Generation (RAG)

  • Vector Databases

  • AI Orchestration Frameworks

• Evaluate and implement emerging AI technologies across enterprise workflows.

Stakeholder Collaboration

• Partner directly with business leaders to translate business requirements into technical solutions.

• Present dashboards, AI strategies, and recommendations to executive leadership.

• Serve as a trusted advisor on analytics, automation, and AI best practices.

Required Qualifications

• 5+ years of Systems Architecture, Data Engineering, Analytics, or Business Intelligence experience.

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Analytics, or related field.

• 5+ years of experience with enterprise analytics and reporting.

• Strong SQL and enterprise data platform experience.

Expert-Level Power BI

• Power BI Dashboard Development

• DAX

• Data Modeling

• Power Query

• Dashboard Performance Optimization

Advanced Excel

• Power Query

• Pivot Tables

• Financial & Operational Modeling

• VBA/Macros (Preferred)

Strong Python Experience

• Data Processing

• Automation

• API Integrations

• Analytics

• Workflow Orchestration

Preferred Qualifications

• Hands-on experience with Generative AI platforms and Large Language Models (LLMs).

• Experience with cloud platforms:

  • Azure

  • AWS

  • Google Cloud Platform (Google Cloud Platform)

• Experience delivering intelligent automation solutions in enterprise or financial services environments.

Agentic AI Experience

Experience with one or more of the following:

• Microsoft Copilot Studio

• LangChain

• LangGraph

• CrewAI

• AutoGen

• Semantic Kernel

• Google ADK

AI Technologies

• Retrieval-Augmented Generation (RAG)

• Vector Databases

• Prompt Engineering

• AI Governance

• AI Evaluation Frameworks

Desired Skills

• Power BI

• Python

• SQL

• Power Query

• DAX

• Excel

• ETL / ELT

• Data Engineering

• Business Intelligence

• AI Automation

• Generative AI

• Agentic AI

• LLMs

• LangChain

• CrewAI

• AutoGen

• Semantic Kernel

• Copilot Studio

• RAG

• Vector Databases

• Azure

• AWS

• Google Cloud Platform