Senior Data Engineer

Responsibilities

• Lead complex data processing initiatives and contribute to large-scale data processing framework projects
• Build and maintain optimized, highly available data pipelines to support enterprise strategy and analytics
• Oversee data integration work, including data modeling, maintaining data warehouses, and writing integration scripts
• Resolve technical and operational challenges through in-depth evaluation of variable factors
• Collaborate with managers and colleagues to resolve engineering issues and achieve strategic goals
• Ensure all data engineering deliverables meet information policies, procedures, and compliance requirements

Requirements

• 4+ years of Data Engineering experience
• Strong expertise in Spark and Scala (including Spark Core, SQL, DataFrames, and Datasets)
• Proficiency in Python or other scripting languages
• Extensive experience with SQL and data warehousing (Oracle, PL/SQL)
• Hands-on experience with Hadoop, Hive, and Autosys
• Experience with NoSQL databases such as MongoDB or Neo4j
• Knowledge of real-time data streaming using Kafka
• Experience with cloud platforms such as GCP, AWS, or Azure
• Proficiency in Unix and Shell scripting

Preferred Qualifications

• Experience developing end-to-end ML/AI pipelines using Apache Spark, H2O, or LLMs
• Exposure to Agentic AI frameworks and GCP Vertex AI
• Familiarity with CI/CD pipelines, infrastructure as code, and cloud deployment best practices
• Experience working in an Agile environment using Scrum or Kanban
• Knowledge of Ab initio or other ETL tools

About the Company

Wells Fargo is a leading financial services company with approximately $2.1 trillion in assets, providing a diversified set of banking, investment, and mortgage products and services globally.