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Tier-1 employer, metro location, popular mid-level Data Analyst title, and broad skill requirements increase candidate competition.
Core SQL, BI, Python skills transferable across industries despite retail domain preference.
Explicit 2-6 years plus mandatory SQL, BI, and analytics tooling implies strict technical filters.
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Collaborate with business leaders to analyze data across multiple domains like Marketing, Merchandising, and Supply Chain to support strategic decision-making.
Develop and maintain reports, dashboards, and basic models tracking business performance using SQL, BI tools, and data platforms such as GCP BigQuery.
Support data pipeline development and ensure accuracy and quality of analytical outputs while communicating findings through AI summaries and data storytelling.
2-6 years overall experience with 1-3 years relevant experience in data analysis.
Bachelor's degree required: B.Tech/B.E or Masters in Statistics/Econometrics/Mathematics or equivalent.
Hands-on experience with SQL including joins and query tuning, and at least one BI Visualization tool (e.g., Power BI, Tableau).
Exposure to large-scale datasets and tools like GCP BigQuery, Spark, and experience with structured (Oracle, Hive) and unstructured (HDFS) databases.
Experienced operating with data analysis frameworks in fast-paced, business-impact environments involving multiple domains such as Retail, Merchandising, and Marketing.
Proficient in technical data skills combined with business understanding to translate analytics into actionable insights and stakeholder communication.
Familiarity with modern data engineering practices, including agile workflows, Git, and AI-powered tools to increase analytical productivity, with some knowledge of Generative AI and Large Language Models.