Lead Data Software Engineer Obeservability and Logging

at  Wells Fargo

APPLICANTS WITH DISABILITIES

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .

Required Qualifications, US:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Proficiency in at least one major programming language (Python preferred)
• Experience writing queries in SQL - with an underlying understanding of query optimization, table design, and the performance trade-offs between various query and database design decisions.
• Hands-on experience with Machine Learning and AI (e.g., Model fine tuning, RAG, grounding etc.

Desired Qualifications:

• Experience analyzing and exploring data - and then visualizing the meaningful parts of that analysis to tell a data-driven narrative.
• Experience interfacing with engineers and management to explain what a data narrative means, how and why you arrived at the conclusions found in said narrative, and explaining any design decisions you made at a high-level so there is a shared understanding.
• Experience with data modeling practices and distributed data processing
• An understanding of how data pipelines are often constructed, and the ability to look at the larger picture and choose between multiple solutions to find one that best fits the business’s requirements.
• Experience working with Pandas, PySpark, BigQuery, and Airflow
• Experience working with containerized environments - e.g., Kubernetes

Wells Fargo is seeking a Lead Data Engineer for the CTO Observability & Logging products which are playing a major role in accelerating the firm’s modernization and move to cloud. In this role the candidate will play a critical delivery role focused on Cloud Observability driving one of Logging’s area product: Data Engineering & Analytics. This role is looking for a candidate that can drive the technical execution and delivery of the strategic enterprise logging product and its integration with the rest of the Observability ecosystem for Cloud based apps products.
As part of this role, the candidate will help lead the migration of 15,000 logging customers (including log data and user developed content) to our strategic Enterprise cloud logging solution. The candidate will also be driving the design and implementation of a new data platform and resulting data lake. Candidate will be part of the Data Engineering team focused on enablement, adoption, analytics, standards & best practices.
This role requires a mix of Software & Data engineering skills and work closely with Product to support our Agile methodology.

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
• Design, develop, and deploy jobs that summarize and normalize large data sets for targeted consumption in a shared data lake leveraging Python or Scala
• Design, develop, and deploy dashboards (PowerBI or other industry standard) to expose data lake data sets to business customers
• 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, US:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Proficiency in at least one major programming language (Python preferred)
• Experience writing queries in SQL - with an underlying understanding of query optimization, table design, and the performance trade-offs between various query and database design decisions.
• Hands-on experience with Machine Learning and AI (e.g., Model fine tuning, RAG, grounding etc.)

Desired Qualifications:

• Experience analyzing and exploring data - and then visualizing the meaningful parts of that analysis to tell a data-driven narrative.
• Experience interfacing with engineers and management to explain what a data narrative means, how and why you arrived at the conclusions found in said narrative, and explaining any design decisions you made at a high-level so there is a shared understanding.
• Experience with data modeling practices and distributed data processing
• An understanding of how data pipelines are often constructed, and the ability to look at the larger picture and choose between multiple solutions to find one that best fits the business’s requirements.
• Experience working with Pandas, PySpark, BigQuery, and Airflow
• Experience working with containerized environments - e.g., Kubernetes.

Job Expectations:

• Able to travel 10% of the time
• Work Schedule: 3 days in office/2 days at home. Schedule is subject to change based on business needs.