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Tier-1 brand, common Data Analyst title, mid-level range, metro location and broad skillset increase competition.
Core SQL, BI and analytics skills are broadly transferable across industries despite retail experience preference.
Explicit 2–6 years requirement plus mandatory SQL, BI, BigQuery and coding exposures make filters strict.
Collaborate with business leaders across multiple domains to turn data into actionable insights that influence strategic decisions.
Execute data analysis, develop reports and dashboards, and apply foundational predictive and diagnostic analytics.
Query and analyze large datasets using SQL and platforms like GCP BigQuery; support data pipeline development and validation.
2-6 years total experience; 1-3 years relevant experience in data analytics.
Bachelor's degree in Engineering (B.Tech/B.E.) or Master's in Statistics/Econometrics/Mathematics or equivalent.
Hands-on experience with SQL including joins and query tuning; knowledge of data warehousing and BI concepts.
Experience with BI visualization tools (Power BI, Looker, Tableau) and data platforms like GCP BigQuery or similar.
Experienced in dealing with large-scale datasets and tools such as Spark, Hive, HDFS, Airflow or similar data pipeline technologies.
Comfortable working in agile environments with Git version control and capable of communicating findings through basic data storytelling.
Has exposure or understanding of retail, merchandising, marketing domains, and familiarity with Generative AI/LLM applications is a plus.