Analyst, Customer Insights BI

KeHE Distributors, LLC•Boulder, CO

5d•Onsite

About The Position

KeHE-a natural, organic, specialty and fresh food distributor-is all about "good" and is growing, so there's never been a more exciting time to join our team. If you're enthusiastic about working in an environment with a people-first culture and an organization committed to good living, good food and good service, we'd love to talk to you!

Requirements

High competency in PowerBI, including DAX expressions, Power Query (M language), data modeling, relationship management, and row-level security implementation
Advanced SQL proficiency for database management, data exploration, stored procedures, transformation logic, and ad hoc reporting
CPG/retail data fluency: Understanding of UPC-level data structures, velocity, ACV, distribution, promotional lift, and market share metrics
Proficiency in MS Office Suite, especially Excel (pivot tables, VLOOKUP, Power Pivot, VBA)
Experience with syndicated data platforms: SPINS, Circana (formerly IRI), Nielsen, or Numerator
Familiarity with retailer data systems (e.g., Kroger 84.51°, Albertsons Plated, retail POS feeds)
Python for data pipeline automation, UPC database management, statistical modeling, and integration scripting (pandas, numpy, requests, etc.)
Analytical mindset with the ability to interpret complex CPG datasets and provide clear, actionable insights for cross-functional stakeholders and executive leadership
Working knowledge of category management concepts (assortment planning, SKU productivity, promotional evaluation) sufficient to support analytical outputs—deep category expertise is not required
Sense of urgency and attention to accuracy and detail in fast-paced, deadline-driven environment
Self-motivated, eager to learn, and focused on continuous improvement of tools and processes
Excellent communication skills: Ability to translate complex data findings into clear, compelling stories for non-technical stakeholders (buyers, sales teams, suppliers)
Strong collaboration skills: Work across multiple departments (Merchandising, Sales, Finance, Marketing, Category Management)
Highly credible, collaborative, and resourceful style with ability to work independently and as a team player
Capable of managing multiple projects simultaneously and prioritizing based on business impact
Bachelor's degree in Computer Science, Data Analytics, Information Systems, Business, Statistics, or related field
4-5 years of experience using BI tools such as PowerBI, Tableau, or Qlik (PowerBI preferred)
2+ years working with CPG/retail datasets, syndicated data platforms, or consumer insights analytics
Proven experience building data models, writing DAX expressions, creating Power Query (M) transformations, and implementing row-level security in PowerBI
Hands-on experience with syndicated data (SPINS, Circana, Nielsen) and ability to manage, map, and manipulate large UPC-level CPG datasets
Ability to remain in a stationary position (seated or standing) for extended periods.
Ability to operate a computer, keyboard, mouse, and other standard office equipment.
Ability to view a computer screen for long periods.
Ability to move about the office occasionally to access files, equipment, or attend meetings.

Nice To Haves

Experience with Tableau or Qlik (in addition to PowerBI)
Azure Data Factory, Databricks, or similar ETL tools for data pipeline automation
SSRS report building for enterprise-grade reporting
Experience in natural/organic foods, specialty grocery, or CPG distribution, preferred
Background supporting Private Label development, innovation pipelines, or white space analysis, preferred
Previous experience working with distributor data or supporting brand/supplier relationships preferred
Knowledge of Exclusive Brands, KeHE portfolio, or specialty food distribution preferred

Responsibilities

Own and manage UPC-level data mapping between CPG syndicated sources (SPINS, Circana, Nielsen), internal KeHE product databases, and the PowerBI data models they feed—ensuring consistency, accuracy, and traceability across all reporting
Build and maintain automated ETL pipelines using Python scripts, SQL stored procedures, and Power Query (M) to ingest, clean, transform, and refresh UPC-level datasets on daily/weekly cadences
Establish and enforce data governance standards for CPG UPC databases—maintaining master product hierarchies, resolving mapping discrepancies, and ensuring data quality across syndicated and proprietary datasets
Design and maintain the centralized data architecture (SQL databases, Python-managed data stores) that serves as the single source of truth for Consumer Insights analytics across cross-functional teams
Automate recurring reports: monthly Brand Intelligence updates, quarterly thought leadership metrics, KPI snapshots for leadership
Reduce manual Excel/PowerPoint workflows through dashboard automation and parameterized reporting
Build alerting systems for KPI thresholds (e.g., velocity drops below 75th percentile, white space opportunities exceeding $1M)
Enable retailer-specific and category-specific parameterized views (e.g., Albertsons Deli dashboard, Publix Cheese performance)
Partner with Consumer Insights Lead to translate analytical frameworks (5-stage white space, promotional lift tools, assortment optimization) into scalable dashboards
Train cross-functional teams (Sales, Merchandising, Marketing, Category Management) on dashboard usage and self-service capabilities
Gather requirements from business stakeholders across Exclusive Brands, Owned Brands, and Import teams
Present insights, tool capabilities, and roadmap updates to senior leadership
Design, build, and maintain 12+ monthly Brand Intelligence dashboards using DAX measures, calculated columns, and Power Query (M) transformations to track brand velocity, promotional lift, and competitive positioning
Create and maintain the underlying data models, relationships, and row-level security configurations that enable self-service white space identification tools across 600+ subcategories
Develop live OKR tracking dashboards for innovation pipeline, Private Label opportunities, and retailer-specific strategic decks
Build predictive assortment optimization models using Monte Carlo simulations and SKU success forecasting