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Common mid-level data analyst title, metro location, and 3–5 year band increase applicant competition.
Data analysis and SQL skills are broadly transferable across industries, reducing background sensitivity.
Explicit 3–5 year requirement plus SQL and data warehouse experience enforce moderate shortlisting filters.
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Gather, analyze and validate data and analytics business requirements using SQL and industry-standard tools.
Maintain data design artifacts including data mapping, business matrices, and transformation rules supporting reporting and analytics.
Leverage generative AI techniques including prompt engineering, RAG, vector and graph databases, and agentic AI concepts to enhance business analysis and data-driven decision-making.
3 to 5 years of experience in business or data analysis with data warehouses or reporting projects.
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or related fields.
Proficiency with SQL and experience in analyzing complex data sets to identify trends and insights.
Experience working in Agile environments and managing multiple priorities with strong communication skills.
Intermediate to advanced capability (2+ years) in incorporating AI-driven analytics techniques and emerging technologies into workflows.
Experience collaborating effectively with cross-functional teams including Product Owners and business stakeholders to design and implement data strategies.
Ability to work successfully in fast-paced, lean organizations using Scaled Agile principles and ways of working.