Data Engineering Senior Manager

Wells Fargo•Charlotte, NC
•$139,000 - $217,000•Hybrid

About The Position

Wells Fargo is seeking a strategic and transformational Data Engineering Senior Manager within Home Lending Data & Insights, a key data engineering organization within Consumer Technology. This role provides engineering leadership across the Capital Markets and Shared Data Services product areas, supporting loan delivery, investor reporting, reusable data capabilities, enterprise data consumption, analytics, artificial intelligence, and risk management. Shared Data Services delivers foundational capabilities including semantic data models, master and reference data management, data distribution patterns, curation frameworks, cloud services, and operational enablement that drive consistency and scale across Home Lending. Capital Markets supports critical business functions related to loan delivery and investor reporting. This leader will be responsible for building and developing high-performing engineering teams, modernizing data platforms, advancing cloud adoption, enabling AI-ready data products, and strengthening engineering standards, governance, resiliency, and operational excellence. The role requires strategic leadership, technical depth, product partnership, and executive influence to deliver business value while operating within a highly regulated financial services environment.

Requirements

  • 7+ years of Data Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education.
  • 3+ years of management or leadership experience.
  • 5+ years of experience leading large-scale data engineering initiatives and enterprise data platforms.
  • 4+ years of experience delivering cloud-based data and analytics solutions.
  • 5+ years of experience in data architecture, data modeling, ETL/ELT, metadata management, data governance, and distributed data processing.
  • 3+ years of experience influencing and collaborating with senior technology and business leaders

Nice To Haves

  • Experience supporting enterprise AI, Machine Learning, Generative AI, or advanced analytics initiatives.
  • Experience with modern cloud data platforms such as Databricks, Snowflake, Azure, AWS, or GCP.
  • Experience with big data and streaming technologies including Spark, Kafka, and related ecosystems.
  • Strong understanding of AI governance, responsible AI principles, and AI model operationalization.
  • Proven ability to lead organizational change and technology transformation initiatives.
  • Experience operating in highly regulated financial services environments.
  • Exceptional executive communication, stakeholder management, and strategic planning capabilities.
  • Advanced degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.

Responsibilities

  • Develop and execute a multi-year data engineering strategy aligned with Wells Fargo's enterprise technology, data, and AI priorities.
  • Partner with senior business and technology leaders to identify opportunities where data and AI can improve customer experiences, operational efficiency, risk management, and business outcomes.
  • Translate business objectives into scalable technology investments and engineering roadmaps.
  • Drive innovation while balancing operational stability, risk management, and regulatory requirements.
  • Champion a data-driven decision-making culture across the organization.
  • Lead the development of AI-ready data platforms that support machine learning, Generative AI, advanced analytics, and intelligent automation initiatives.
  • Partner with Data Science, Analytics, Risk, Product, and Architecture teams to accelerate AI adoption and operationalize enterprise-scale AI solutions.
  • Establish best practices for data accessibility, model readiness, data quality, lineage, governance, and responsible AI.
  • Evaluate emerging technologies and identify opportunities to leverage AI and automation to improve engineering productivity and business outcomes.
  • Drive adoption of modern data architectures that support real-time analytics, predictive insights, and AI-driven decision-making.
  • Lead, mentor, and develop high-performing teams of data engineers, engineering managers, and technical leaders.
  • Create an inclusive culture focused on accountability, innovation, collaboration, and continuous learning.
  • Build organizational capability through coaching, succession planning, and leadership development.
  • Attract, retain, and develop top engineering talent.
  • Foster engineering excellence through modern software engineering practices, automation, DevOps, and Agile methodologies.
  • Oversee the design, development, and support of enterprise-scale data platforms, data lakes, streaming solutions, and cloud-native data architectures.
  • Ensure solutions are scalable, reliable, secure, and compliant with enterprise standards.
  • Drive platform modernization initiatives utilizing cloud technologies, automation, and reusable engineering patterns.
  • Establish standards for data quality, observability, metadata management, resiliency, and operational excellence.
  • Partner with architecture and security teams to ensure alignment with enterprise technology standards.
  • Ensure compliance with Wells Fargo's risk management framework, information security policies, and regulatory requirements.
  • Promote strong data governance, controls, lineage, privacy, and stewardship practices.
  • Lead engineering teams through audits, regulatory reviews, and remediation efforts as required.
  • Balance innovation with sound operational risk management and governance principles.

Benefits

  • Information about Wells Fargo's US employee benefits
  • Information about Wells Fargo's International employee benefits
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