Lead Quantitative & Data Analytics Specialist

Wells Fargo

Confirmed live yesterday High trust
Closes in 2 days Hybrid

Quick summary

Work type
Hybrid
Location
CHARLOTTE, NCCHANDLER, AZ
Posted
4 days ago
Freshness
Confirmed live yesterday
Closes
Sep 29, 2026 (soon)

Market check

Salary context

How this pay compares to similar roles

Similar $168k
$124k most similar roles pay here $211k

This listing doesn't post a salary. Most similar roles pay $135,000–$200,550.

Based on 240 similar postings.

Employer

About Wells Fargo

Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services

Wells Fargo currently has 40 open roles on FindRole.

Listed pay typically runs $159,000–$279,000 across 21 roles with salary data.

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At a glance

TL;DR · Lead Quantitative & Data Analytics Specialist

Lead Quantitative & Data Analytics Specialist will join the Enterprise Functions Technology group to lead the design, development, and modernization of data platforms supporting Enterprise Finance Analytical Reporting. This role involves providing technical leadership for a high-performing engineering team while building scalable data pipelines, batch and streaming integration solutions, and AI-ready data architectures. The position focuses on creating semantic data layers to support Generative AI, Retrieval-Augmented Generation, and Agentic AI capabilities. Key responsibilities include improving data quality, lineage, and observability while managing cloud modernization initiatives. Required skills include expertise in Python, SQL Server, and data modeling for ETL/ELT processes. Candidates should be proficient with CI/CD tools like GitHub and Harness, and possess experience with OpenShift Container Platform. The role solves complex problems regarding enterprise knowledge management through well-governed, metadata-driven assets and advanced analytics capabilities.

What you'll do

  • Lead the design, development, and modernization of enterprise data, analytics, and reporting platforms.
  • Provide technical leadership and mentorship while promoting engineering best practices and AI-assisted development.
  • Design and build scalable data pipelines, including batch, streaming, and event-driven integration solutions.
  • Develop governed, reusable data assets to improve quality, lineage, observability, and performance.
  • Support cloud modernization initiatives and the migration of legacy data systems.
  • Build data architectures and semantic layers to enable Generative AI, LLM, and RAG capabilities.
  • Enable Agentic AI through metadata-driven, well-governed data assets and context engineering.
  • Establish governance standards to ensure compliance with security and regulatory requirements.

What we're looking for

  • Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
  • 5+ years of Quantitative Analytics experience or equivalent through work, training, military experience, or education.
  • 5+ years of experience building and supporting large-scale data pipelines, data integration frameworks, and data platforms.
  • 5+ years of solution engineering experience applying mathematical approaches to technical design.
  • Experience in Data Engineering (preferred).
  • Experience working in Agile, Scrum, or Kanban environments (preferred).
  • Proficiency with CI/CD and DevOps tools including GitHub and Harness (preferred).
  • Strong programming and database experience with Python and SQL Server (preferred).

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