Lead Data Engineer - PySpark/SQL/AI

About This Role Wells Fargo is seeking a Lead Data Engineer

In This Role, You Will

• Lead complex initiatives with broad impact and act as key participant in large scale software planning for the Technology area
• Design, develop, and run tooling to discover problems in data and applications and report the issues to engineering and product leadership
• Review and analyze complex software enhancement initiatives for business, operational or technical improvements that require in depth evaluation of multiple factors including intangibles or unprecedented factors
• Make decisions in complex and multi-faceted data engineering situations requiring understanding of software package options and programming language and compliance requirements that influence and lead Technology to meet deliverables and drive organizational change
• Strategically collaborate and consult with internal partners to resolve highly risky data engineering challenges

Required Qualifications:

• 5+ years of Database Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• 5 - 10+ years of experience in Data Engineering and Enterprise Data Platforms.
• 5+ years leading enterprise-scale data modernization initiatives.

• Strong hands-on expertise with:

• Python
• Apache Spark / PySpark
• SQL
• ETL/ELT Design

• API Integration

• Deep understanding of:

• Lakehouse Architecture
• Medallion Architecture
• Data Warehousing Concepts
• Data Governance
• Metadata Management

• Data Quality Frameworks

• Proven experience with any cloud platforms:

• Azure
• Microsoft Fabric
• Databricks
• GCP

• Experience migrating large-scale data environments from on-premise to cloud.

• Experience in HR, Workforce, Talent, Payroll, or Enterprise Data domains.
• Exposure to AI/ML, Generative AI, Agentic AI, and LLM-based application development.
• Experience implementing Data Products, Data Mesh, and Self-Service Analytics platforms.
• Knowledge of Kubernetes, Docker, Terraform, and Infrastructure as Code.
• Familiarity with MLOps, DataOps, and DevSecOps practices.
• Cloud certifications in Azure, Databricks, GCP, or equivalent.

**Job Expectations:** We are seeking a highly experienced Modern Data Engineering Lead to drive the modernization of HR Data platforms and accelerate the adoption of Cloud, AI, and Data Engineering best practices . This role will lead the transformation of large-scale legacy data ecosystems into scalable, cloud-native, AI-enabled platforms while enabling advanced analytics, data products, automation, and self-service capabilities.

The ideal candidate will possess deep expertise in Cloud Data Platforms, Lakehouse Architecture, Data Migration, AI-powered Engineering, Python, Spark, API integration, and Enterprise Data Modernization . This leader will work closely with business stakeholders, architects, product teams, and engineering organizations to deliver strategic outcomes across HR Data systems.

Data Platform Modernization

• Lead enterprise-scale modernization initiatives from legacy data warehouses and ETL platforms to cloud-native data ecosystems.
• Design and implement modern Lakehouse architectures using Medallion (Bronze, Silver, Gold) data design principles.
• Develop scalable and secure data platforms supporting batch, streaming, and real-time processing workloads.
• Drive architecture decisions involving Data Lake, Data Warehouse, Lakehouse, Data Mesh, and Data Fabric patterns.

Cloud & Data Engineering

• Design, develop, and optimize large-scale data pipelines using:

• Python
• Apache Spark / PySpark
• SQL

• ETL/ELT frameworks

• Implement cloud-native solutions leveraging platforms such as:

• Microsoft Fabric
• Establish engineering standards for reliability, scalability, observability, and cost optimization.

Data Migration & Transformation

• Lead large-scale migration programs involving:

• Legacy Data Warehouses
• On-Prem Hadoop/Cloudera Platforms

• Traditional ETL Middleware

• Develop migration strategies including assessment, planning, automation, reconciliation, testing, and cutover execution.
• Ensure business continuity and data integrity during migration programs.

Posting End Date: 29 Aug 2026

• Job posting may come down ea…