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Strong brand, popular data analyst title, metro location, and broad technical requirements drive high competition.
Analytical tooling (SQL, Python, BI) is highly transferable across industries, so background sensitivity is low.
Explicit 5-8 years plus mandatory SQL, BI, Python, BigQuery and GenAI skills increase filtering strictness.
Collaborate with business leaders to transform data into actionable insights supporting strategic decisions across multiple domains such as Marketing, Supply Chain, and Finance.
Develop and deliver advanced analytics and AI-driven solutions including Generative AI techniques to support decision-making, forecasting, optimization, and automation.
Build and maintain scalable analytical workflows and data pipelines using tools like GCP BigQuery, Spark, SQL warehouses, and Airflow while ensuring accuracy and alignment with business context.
5-8 years overall experience with 3-5 years in relevant data analytics roles.
Bachelor's degree in a quantitative field such as B.Tech/B.E., Statistics, Econometrics, Mathematics, Data Sciences, Computer Science or equivalent.
Proficiency with SQL, SQL optimization, data warehousing concepts, BI visualization tools (Power BI, Looker, Tableau), and large datasets technologies (Teradata, Oracle, Hive, HDFS).
Hands-on experience with R, Python, Hive or similar; knowledge of advanced analytics techniques (regression, time-series, classification).
Experienced in integrating and operationalizing AI-driven analytics solutions including Generative AI and LLM-based tools to scale business insights and automation.
Strong ability to translate complex business problems into structured analytical questions and communicate insights effectively to non-technical stakeholders.
Comfortable working in fast-paced, agile environments handling large-scale datasets across retail or related domains such as Merchandising and Marketing.