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Common mid-level data analyst role, broad required skills, and metro appeal increase applicant competition.
Core analytics skills like SQL, Python, and BI are highly transferable across industries.
Explicit 3–5 years plus mandatory SQL, Python, and PowerBI requirements create strict screening for candidates.
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Develop and maintain scalable data infrastructure and models for global sales business intelligence, including SQL/ETL queries and automated reporting.
Manage small to medium projects by gathering business requirements, coordinating with IT and stakeholders, and delivering data-driven solutions.
Analyze complex data sets to generate insights, KPIs, forecasts, and support sales and commercial operations performance measurement.
Bachelor's degree or equivalent in computer science, statistics, mathematics, information systems, engineering, or related field.
3-5 years experience in data operations with hands-on analytics development.
Experience with SQL, Python/R, PowerBI, and Excel; skilled in building star schema data models and data warehousing concepts.
Fluent in English; strong communication and leadership skills.
Experienced in applying quantitative analysis and data mining to complex, large data sets for business insights in sales/commercial environments.
Operates with a critical thinking and execution mindset, balancing effort and return, and automates tasks to scale solutions.
Effective in stakeholder management and cross-functional collaboration to influence and deliver timely business intelligence outcomes.