Senior Data Analyst - Analytics and Automation

New
W
Welo GlobalFinance Technology
MexicoFull-TimeSenior
Salary not disclosed
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Job Details

Languages
Fluent English, spoken and written.
Experience
5-10 years of relevant experience
Required Skills
PythonSQLBusiness IntelligenceData AnalysisETLRESTful APIsData modeling

Requirements

  • 5-10 years of relevant experience in a hands-on analytics or data role.
  • Advanced proficiency in SQL, including joining tables, validating schemas, and performance tuning.
  • Practical Python proficiency for data transformation, analysis, and automation.
  • Strong understanding of ETL/ELT design, data requirements gathering, and pipeline validation.
  • Proven experience building end-to-end reporting and analytical experiences in BI platforms (e.g., Power BI) or custom HTML/web-based reports.
  • Demonstrated history of automating manual, recurring data and reporting workflows.
  • Advanced Excel skills, with the ability to deconstruct and document legacy workbooks.
  • Strong investigative instincts for exploratory data analysis and hypothesis testing.
  • Ability to learn and adopt new AI-assisted tools and workflows quickly.
  • Fluency in spoken and written English for collaboration with global business and technical leadership.
  • Bachelor's degree in Computer Science, Data Science, or a related quantitative field preferred.

Responsibilities

  • Partner with FP&A leadership to identify opportunities to fundamentally change reporting and analytical processes.
  • Reverse-engineer complex legacy Excel workbooks and manual processes to map business logic and data sources.
  • Design and build automated solutions using SQL, Python, ETL, APIs, and modern AI tools.
  • Resolve data quality, mapping, and reconciliation issues across large, multi-system datasets.
  • Develop interactive, AI-assisted dashboards and HTML-based reporting tools.
  • Build driver-based analysis and proactive exception-reporting workflows.
  • Collaborate with Data Engineering on infrastructure standards and data pipeline requirements.
  • Develop and shape documentation, conventions, and workflows for the internal FP&A AI repository.
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