Lead Software Engineer- Data & Analytics

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

The Wells Fargo Consumer Lending Technology (CLT) Head of Data has been tasked with transforming and modernizing operational and analytic data across Consumer Lending. The mission for CLT Data is to implement best in class engineered technologies and best practices that are Agile-minded, commercially structured, compliance-oriented, and focused on the rapid delivery of high-quality, safe products and services which are consumable at scale across Consumer Lending lines of business.

The Lead Software Engineer – Data & Analytics role will report directly to the CLT Data Engineering Manager. The role will be responsible for providing technical leadership for the data engineering team, solution designing of medium to complex data products, hands-on development of reusable frameworks, perform design and code reviews, driving and accelerating Data and Analytics Strategy & Roadmap across Consumer Lending.

Key responsibilities include:

• Define and implement Data Strategy for private and public cloud
• Lead and perform current state data assessments, create future state vision, strategy, roadmap
• Partner with Enterprise Data Services organization on Enterprise Data Strategy
• Ensure Data-related design patterns, best practices are front and center of technology practices in the organization.
• Create and manage reusable frameworks for data engineering and establish architecture patterns for data engineering across traditional and big-data solutions
• Proven hands-on development expertise in Data warehousing ETL stack and Big Data Hadoop technology stack including Hadoop, Hive, Python, Java/Scala, SPARK,
• Expert level experience in Business Intelligence and Analytics capabilities like Tableau, ESSBASE, AtScale, Thoughtspot etc
• Advanced level expertise in building high performance data and analytical products
• Ability to conduct technical training sessions for technical and line of business users

This role will also work closely with the rest of the CLT Data & Analytics Engineering & Architecture team as well as Wells Fargo CTO, Enterprise Data teams.

Other responsibilities/experience needed for this role include:

• Partner with Enterprise data teams and Line of Business partners on customer-centric view of the data, data reuse, and data consistency across all customer interactions

• Collaborate with Enterprise Data organization on supplying and governing Consumer Lending data going into the Enterprise Data Lake
• Establish processes and tools to support consistency, lineage, collection, processing, sharing, and organization of data across entire Consumer Lending portfolio
• Establish Consumer Lending wide data standards and governance. Manage data as a strategic asset and operationalize data governance, data quality, and controls across the organization
• Introduce and propagate modern Engineering practices around Data including automation of data-related processes
• Drive consistency, efficiencies, and cost benefits through Data Integration practices and standards

• Experience driving significant maturity improvements in low-maturity technology environments – experience consulting teams, collaborating across enterprise to mature technology solutions, delivering modern capabilities, and/or delivering in Agile environment.

Required Qualifications, US:

• 5+ years of Software Engineering experience especially in Data & Analytics domain, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 3+ years of technical leadership or architecture experience, in a data and technical environment
• 3+ years of experience leading in the Data Engineering, Data Management, SQL Server, SSIS ETL, Tableau
• A Bachelor’s degree or higher in computer science or engineering
• End-to-End data, analytics and machine learning technology and business acumen including Data Warehousing, ODS, Big Data platforms and related technology stack such as SQL Server, SSIS ETLs, Cloudera, Python, Spark, Hive and cloud native data capabilities.
• Ability to implement data and analytics capabilities and mindset at scale

• Desired Qualifications:
• A Master’s Degree in Data Science, Statistics or relevant field
• 5+ years’ software engineering experience as well as demonstrated experience in Big Data Engineering, Application Support and/or Technology Operations
• 3+ years of experience with Agile practices
• 3+ years’ experience with Data architecture, design, and management