Lead Data Engineer
Wells Fargo1 day ago
Responsibilities
- Lead the design and implementation of enterprise-scale data platforms and solutions.
- Develop scalable data ingestion, transformation, enrichment, distribution, and ETL/ELT frameworks.
- Design and maintain enterprise data models, data architecture standards, and integration frameworks.
- Develop event-driven data processing solutions using streaming and messaging technologies.
- Create and optimize SQL-based solutions for analytics, reporting, troubleshooting, and operational processing.
- Partner with cybersecurity, technology risk, architecture, engineering, and business teams on strategic data capabilities.
- Support analytics, AI-enabled services, enterprise reporting, and enterprise workflow solutions.
- Lead technical design activities, architecture reviews, engineering best practices, and continuous improvement initiatives.
- Research and resolve complex production issues while maintaining platform stability, scalability, and performance.
- Mentor and provide technical guidance to data engineers throughout the development lifecycle.
- Use AI-assisted development and analysis tools responsibly while accounting for model limitations, security, compliance, privacy, and operational risks.
Requirements
- At least 5 years of database engineering experience, or equivalent demonstrated through work experience, training, military experience, or education.
- Strong expertise in data modeling, data architecture, and enterprise data integration patterns.
- Strong experience developing and optimizing complex SQL queries and database solutions.
- Experience building scalable ETL/ELT pipelines and data ingestion frameworks.
- Experience integrating with ServiceNow and enterprise workflow platforms.
- Preferred experience includes cybersecurity, technology risk, governance, risk and compliance, enterprise reporting, analytics, and data consumption solutions.
- Preferred experience includes OpenShift, Kubernetes, cloud platforms, NoSQL databases, graph databases, Redis, distributed caching, Oracle, Kafka, Liquibase, Apache Iceberg, PySpark, and large-scale data warehouses.
- Preferred experience includes AI-enabled data services, Generative AI, Retrieval-Augmented Generation, machine learning platforms, data governance, metadata management, data lineage, audit capabilities, and master data management.
- Preferred experience includes enterprise API integrations, event-driven architectures, cloud migration, platform modernization, and regulated financial services environments.
- Ability to solve complex data engineering challenges, collaborate cross-functionally, and provide technical leadership, mentoring, and guidance.
Tech Stack
Categories
Data Engineering
About Wells Fargo
Wells Fargo & Company is a U.S.-based financial services firm providing consumer and commercial banking, mortgages, credit, and wealth/investment services to individuals, small businesses, and enterprises. It earns revenue from interest income and fees across retail banking, payments, lending, and capital markets. Founded in 1852 and headquartered in San Francisco, it is publicly traded on the NYSE (WFC) and operates nationally with offices in multiple countries.