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Wells Fargo is seeking a Lead Software Engineer (Data Engineering/Generative AI). The Finance Technology Team within Enterprise Functions Technology (EFT) is seeking a Lead Software Engineer to join our Profit View team at Wells Fargo. As a Lead Software Engineer in the Profit View Data Engineering team, candidate will play a pivotal role in the design, development, and maintenance of our metadata-driven data engineering frameworks. Candidate will work independently to deliver critical project tasks, focusing on building, enhancing, and troubleshooting robust data pipelines, APIs, Gen AI solutions and wrapper capabilities for the Profit View project. This role is essential for ensuring best development practices and strong validations during, Modernization of our current tech stack, Gen AI solution that we are building, Data Center exit migrations and DPC onboarding. Candidate will collaborate with cross-functional teams to drive the implementation of scalable, high-performance data solutions using Python, Java, Gen AI, SQL, Apache Spark, Iceberg, Dremio, Power BI and Autosys. Enterprise Finance & Technology is a collaborative, cross-functional, Agile organization that is looking for independent thinkers willing to drive innovative solutions for business problems through Gen AI, data delivery and data management.
Job Responsibility:
Lead complex technology initiatives including those that are companywide with broad impact
Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines
Design, code, test, debug, and document for projects and programs
Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors
Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives
Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals
Lead projects, teams, or serve as a peer mentor
Requirements:
5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Demonstrate in-depth understanding of Data Warehousing (DWH) concepts
Strong experience in large data transformation projects
Experience designing and optimizing solutions for high-volume batch processing
Good experience on Unix Shell scripting
At least 6 years of experience working with any RDBMS
At least 6 years of experience in building big data pipelines
At least 5 years of experience working with Apache Spark, Java, Hive, Hadoop and GCP
At least 2+ years of experience in using LLMs for automation
Strong experience with programming in Python, Java, SQL and good understanding of bash scripting for data processing and automation
Hands-on experience with Apache Spark for large-scale data processing
Experience with Autosys or similar job scheduling/orchestration tools
Experience in working with CI/CD pipelines, improving code coverage and vulnerability remediation
5+ years of experience in Agile mode of working
Decent understanding on workings of Rest APIs, Dremio and Object store
Proven ability to independently deliver complex project tasks and solutions
Solid understanding of data engineering best practices, including validation and quality assurance
Excellent troubleshooting and problem-solving skills
Proficiency in data modeling and database design
Experience in working with Open table formats like (Iceberg, Delta)
Knowledge of data governance, security, and compliance requirements
Hands on Experience with GenAI use cases
Experience with cloud data platforms (e.g., AWS, Azure, GCP)
Exposure to financial services or Commercial and corporate investment banking domains