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WF
WF
51 – 200 Employees
B2BConstruction
WF International Limited (WXM), known as WF, provides commercial HVAC, floor-heating, and water-purification solutions for large-scale commercial and industrial projects. Since 2009, the company has supported high-rise developments, metro systems, hotels, hospitals, and manufacturing facilities through project delivery, product distribution, and maintenance services. WF is an exclusive distributor for brands including Toshiba, Gree, and AO Smith, with a focus on energy-efficient installations, sustainable systems, and long-term service agreements. As a Nasdaq-listed company, WF operates within U.S. SEC governance and financial-reporting requirements.
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Lead Quantitative Data Analytics Specialist

Lead modernization of Wells Fargo’s enterprise finance data engineering and analytics platforms. Build scalable pipelines and AI-ready architectures for Generative AI, retrieval-augmented generation, and agentic solutions.

USUnited StatesAZArizonaNCNorth CarolinaHybridFull-timeSeniorEnglish RequiredAnalytics Engineer
CloudETLMicroservicesOpenShiftPythonSQL

Description

  • Own the design, development, and modernization of enterprise data, analytics, and reporting platforms
  • Provide technical direction, architecture guidance, and mentorship while advancing engineering standards and AI-assisted development
  • Build scalable data pipelines, data products, and batch, streaming, and event-driven integration solutions
  • Create governed, reusable data assets while strengthening data quality, lineage, observability, and platform performance
  • Contribute to cloud modernization programs and legacy data solution migrations
  • Develop data architectures and semantic layers that support advanced analytics, Generative AI, LLM, and RAG use cases
  • Enable agentic AI and context engineering with discoverable, metadata-driven, well-governed data assets
  • Collaborate with business, technology, and AI teams to deliver scalable, secure, and compliant data and analytics solutions
  • Define governance standards, uphold security and regulatory requirements, and improve operational efficiency and cost management
  • Lead a high-performing engineering team and work closely with stakeholders, architects, data scientists, AI engineers, and product owners

Requirements

  • At least five years of quantitative analytics experience, or equivalent experience, training, military experience, or education
  • At least five years of experience building and supporting large-scale data pipelines, integration frameworks, and data platforms
  • At least five years of solution engineering experience applying mathematical methods to technical design
  • Bachelor’s degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
  • Data engineering experience or equivalent experience, training, military service, or education
  • Experience working in Agile, Scrum, or Kanban environments
  • Proficiency with CI/CD and DevOps tools, including GitHub and Harness
  • Experience developing with Python
  • Experience using Devin, Claude, Cursor, Wisdom AI, Rogo, or Tachyon
  • Strong hands-on knowledge of SQL Server database design, development, and optimization
  • Experience designing and developing enterprise-scale data pipelines and integration solutions
  • Experience creating scalable data engineering solutions involving data modeling, data warehousing, ETL/ELT, and pipeline orchestration
  • Strong Python and SQL Server programming and database experience for data integration, transformation, and analytics
  • Experience building APIs, microservices, and event-driven architectures
  • Knowledge of data quality, governance, metadata management, and data lifecycle practices
  • Experience using AI-assisted engineering tools and methods, including GitHub Copilot, prompt engineering, AI-generated code, testing, and documentation
  • Experience developing and deploying cloud-native solutions on OpenShift Container Platform (OCP)
  • Ability to work in an office and not eligible for visa sponsorship.
  • benefits

Benefits

  • Hybrid work schedule
  • Equal opportunity employment
  • Medical accommodation support during recruitment or interview
  • Drug-free workplace

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