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Tier-1 brand, mid-level generalist data role, metro location, and broad technical requirements increase competition.
Core analytics skills transfer across industries, but retail domain and GenAI experience increase role specificity.
Explicit 5–8 years requirement plus mandatory SQL, BI tools, BigQuery, Python/R, Airflow and analytics techniques.
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Translate complex business problems into analytical questions and deliver AI-driven decision support, forecasting, optimization, and automation solutions.
Partner with business stakeholders to validate requirements and present actionable insights that influence strategic decisions.
Build and maintain scalable data pipelines and analytical workflows using platforms like GCP BigQuery, Spark, SQL, and orchestration tools such as Airflow.
5-8 years overall experience with 3-5 years in relevant data analytics roles.
Bachelor's or Master's degree in quantitative fields such as B.Tech/B.E, Statistics, Econometrics, Mathematics, Data Sciences, or Computer Science.
Strong proficiency in SQL, SQL optimization, and data warehouse/BI concepts plus hands-on experience with BI visualization tools (Power BI, Looker, Tableau).
Experience with large-scale structured and unstructured data platforms (Teradata, Oracle, Hive, HDFS) and advanced analytics techniques (regression, time-series, classification).
Experienced in applying advanced analytical and AI techniques including Generative AI (GenAI) and LLM-based solutions to enhance data analysis and automate insights.
Comfortable working in fast-paced, agile environments integrating AI-agent workflows for end-to-end analytics automation and productivity scaling.
Has domain experience or strong understanding of Retail, Merchandising, or Marketing data contexts to translate complex problems into business impact.