Sr Data Analyst

Target · Tower 02

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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:


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 

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


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