Lead Quantitative and Data Analytics Specialist

Wells Fargo

. Lead the design, development, and modernization of enterprise data, analytics, and reporting platforms .

Posted 9/23/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing scalable data architectures, data pipelines, and analytics solutions while ensuring data quality and compliance. Proficient in leveraging AI-assisted engineering tools and methodologies to enhance data integration and operational efficiency.

Highest-signal resume keywords

Quantitative Analytics ExperienceData Engineering ExperienceSolution Engineering ExperienceProficiency in PythonExperience with CI/CD and DevOps Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentData Integration FrameworksData ModelingETL/ELT ProcessesSQL Server OptimizationAPI DevelopmentMicroservices ArchitectureEvent-Driven ArchitectureData GovernanceData Quality Management

Soft Skills

Technical LeadershipMentorshipCollaborationCommunication

Tools & Technologies

GitHubHarnessOpenShift Container PlatformAI-Assisted Engineering Tools

Industry Keywords

AgileScrumKanbanCloud ModernizationData Lifecycle Management

Tech Stack

Tools & technologies

CloudETLMicroservicesOpenShiftPythonSQL

About the role

Key responsibilities & impact

Lead the design, development, and modernization of enterprise data, analytics, and reporting platforms
Provide technical leadership, architecture guidance, and mentorship while promoting engineering best practices and AI-assisted development
Design and build scalable data pipelines, data products, and batch, streaming, and event-driven integration solutions
Develop governed, reusable data assets and improve data quality, lineage, observability, and platform performance
Support cloud modernization initiatives and migration of legacy data solutions
Build data architectures and semantic data layers enabling advanced analytics, Generative AI, LLM, and RAG capabilities
Enable Agentic AI and Context Engineering through discoverable, metadata-driven, and well-governed data assets
Partner with business, technology, and AI teams to deliver scalable, secure, and compliant data and analytics solutions
Establish governance standards, ensure security and regulatory compliance, and drive operational efficiency and cost optimization
Lead a high-performing engineering team and collaborate with business stakeholders, architects, data scientists, AI engineers, and product owners

Requirements

What you’ll need

5+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of: work experience, training, military experience, education
5+ years of experience building and supporting large-scale data pipelines, data integration frameworks, and data platforms
5+ years of solution engineering experience, specifically applying mathematical approaches to technical design
Bachelor's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
Data Engineering experience or equivalent demonstrated through work experience, training, military service, or education
Experience working in Agile, Scrum, or Kanban environments
Proficiency with CI/CD and DevOps tools, including GitHub and Harness
Experience developing solutions using Python
Experience with Devin, Claude, Cursor, Wisdom AI, Rogo, or Tachyon
Strong hands-on knowledge with SQL Server database design, development, and optimization
Experience designing and developing enterprise-scale data pipelines and data integration solutions
Experience designing and developing scalable data engineering solutions, including data modeling, data warehousing, ETL/ELT processes, and data pipeline orchestration
Strong programming and database experience with Python and SQL Server for data integration, transformation, and analytics
Experience building APIs, microservices, and event-driven architectures
Knowledge of data quality, data governance, metadata management, and data lifecycle best practices
Experience leveraging AI-assisted engineering tools and practices, including GitHub Copilot, prompt engineering, AI-driven code generation, testing, and documentation
Experience developing and deploying cloud-native solutions using OpenShift Container Platform (OCP)
Ability to work in office
Not eligible for visa sponsorship

Benefits

Comp & perks

Hybrid work schedule
Relocation assistance is not available for this position