Sr Data Analyst - Fp&a Reporting & Analytics

Target Target · Retail · Minneapolis, MN

This role is for a Sr. Data Analyst in Financial Planning & Analysis (FP&A) at Target, focusing on reporting and analytics. The analyst will partner with finance leaders to design, automate, and enhance reporting solutions using SQL, Python/R, and data visualization tools like Power BI, Looker, or Tableau. The role requires experience with forecasting models, statistical analysis, and strong communication skills to translate data insights for business stakeholders. It is a hybrid role based in Minneapolis, MN.

What you'd actually do

  1. You’ll play a key role in delivering standardized, accurate, and insightful financial reporting across FP&A.
  2. This role partners closely with finance leaders and business stakeholders to design, automate, and enhance reporting solutions that drive data-informed decision-making.
  3. As part of a centralized Reporting & Analytics team, this analyst will support multiple FP&A functions (Merch Finance, Marketing, Stores, Supply Chain, Corporate Finance, Capital) by providing scalable reporting, dashboarding, and analytical insights.

Skills

Required

  • Advanced SQL experience writing complex queries
  • Intermediately accomplished with Python or R
  • Knowledge of forecasting models including statistical analysis
  • Advanced data visualization skills; building interactive, executive ready dashboards in tools like Power BI, Looker, Tableau, etc.
  • Solid problem solving, analytical skills, data curiosity, data mining, data creation and consolidation
  • Support conclusions with a clear, understandable story that leverages descriptive statistics, basic inferential statistics, and data visualizations
  • Willingness to ask questions about business objectives and the measurement needs for a project workstream, and be able to measure objectives & key results
  • Excellent communication skills with the ability to speak to both business and technical teams, and translate ideas between them
  • Experience in analytics tools such as: SQL, Excel, Hadoop, Hive, Spark, Python, R, Domo, Adobe Analytics (or Google Analytics) and/or equivalent technologies