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Sr Data Analyst

Target · Tower 02, Manyata Embassy Business Park, Racenahali & Nagawara Villages. Outer Ring Rd, Bangalore 540065

On-site / hybridData Analytics / BI 1 day ago

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About the job

Skills mentioned in this posting (23)

PythonSQLAIGitAgileAutomationGCPData AnalysisTableauAnalyticsSparkAirflowLLMsGenerative AIStatisticsData WarehousingLookerBigQueryHadoopOracleRAGPrompt EngineeringForecasting

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As a Sr Data Analyst for Target’s Data Analytics team you’ll:    Support our world-class leadership team at Target with critical data analysis that helps business team to make profitable decisions. Enable faster, smarter and more scalable decision-making to compete and win the modern retail market. Collaborate with stakeholders and understand their priorities/roadmap to drive business strategies using data. Key Responsibilities: - Translate business problems into well-defined analytical questions and structured approaches - Support scenario, decision, and action modelling to evaluate business trade-offs and inform recommended actions - Partner with Target business stakeholders to understand priorities and roadmaps, validate analytical requirements, and present insights and recommendations with clarity and impact - Develop and deliver analytical and AI-driven solutions (including GenAI, Agent, and Agentic approaches) that enable decision support, forecasting, optimization, and automation - Apply advanced analytics techniques, including causal, predictive, and prescriptive analytics, to drive deeper understanding of business levers and inform optimal actions - Work with large-scale datasets using platforms such as GCP BigQuery, Spark, and SQL-based data warehouses; build and maintain reliable data pipelines using Airflow or similar orchestration tools - Contribute to AI-driven analytical workflows, defining quality metrics (e.g., accuracy, relevance), assessing reliability, and measuring tangible business impact - Ensure analytical outputs are accurate, scalable, and aligned with business context - Develop strong data storytelling skills to communicate insights and recommendations to non-technical audiences - Document analytical methodologies, assumptions, and outputs to support reuse and knowledge sharing - Adhere to corporate data protection standards and responsible AI practices Requirements / About You:             Experience: Overall 5-8 years exp and relevant 3-5 years exp             Qualification:                         TI : B.Tech / B.E. or Masters in Statistics /Econometrics/Mathematics equivalent                         US : BA/BS in a quantitative degree – Math, Statistics, Econometrics, Data Sciences, Computer Science or equivalent work experience Skills required: 1.     Extensive exposure to Structured Query Language (SQL), SQL Optimization and DW/BI concepts. 2.     Proven hands-on experience in BI Visualization tool (i.e. PBI, Looker, Tableau) with ability to learn additional vendor and proprietary visualizations tools. 3.     Strong knowledge of structured (i.e. Teradata, Oracle, Hive) and unstructured databases including Hadoop Distributed File System (HDFS). Exposure and extensive hands-on work with large data sets. 4.     Hands on experience in R, Python, Hive or other open-source languages/database  - Hands on experience in any advanced analytical techniques like Regression, Time-series models, Classification Techniques, etc. and conceptual understanding of all the techniques mentioned above - Git source code management & experience working in an agile environment. 7.     Strong attention to detail, excellent diagnostic, and problem-solving skills 8.     Highly self-motivated with a strong sense of urgency to be able to work both independently and in team settings in a fast-paced environment; capability to manage urgency timelines 9.     Competent and curious to ask questions and learn to fill gaps, desire to teach and learn. 10.  Excellent communication, service orientation and strong relationship building skills 11.  Experience with Retail, Merchandising, Marketing will be strong addons 12.  Hands-on experience leveraging Generative AI (GenAI) and LLM-based solutions (e.g., prompt engineering, Retrieval-Augmented Generation – RAG) to enhance data analysis, automate insight generation, and support business decision-making 13.  Ability to integrate AI-driven tools and AI-agent workflows into end-to-end analytical processes, enabling automation, improving productivity, and scaling analytics use cases. Useful Links- Life at Target- https://india.target.com/ Benefits- https://india.target.com/life-at-target/workplace/benefits Know More About Us here:   - Life at Target : https://india.target.com/   - Benefits : https://india.target.com/life-at-target/workplace/benefits   - Culture : https://india.target.com/life-at-target/belonging   - Target Tech : https://tech.target.com/