LEAD DATA ANALYST, SCORe SUPPLY CHAIN (P4018) / HM: Katie Mendrala

Summary 

The SCORe (Supply Chain, Operations, and Replenishment) team is looking for a Lead Data Analyst. This role will support end-to-end supply chain workstreams with a focus on enabling supply chain and inventory data. Ideal candidates will bring a focus of business acumen in the Supply Chain and Inventory Replenishment industry. Familiarity with 84.51° and Kroger’s Supply Chain and Operations data assets is preferred.

This Lead data scientist role for Supply Chain specifically focuses on supporting data needs in the Inventory Replenishment, Transportation, and warehouse spaces. This includes bringing in new data, diagnosing data issues, and improving data quality within these domains. 

As a Lead Data Analyst,you are joining a cross-functional technical community of analysts, data scientists, product owners, program leads and software engineers. Your superpower is data expertise, and your passion lies in enabling others to understand and use data to appropriately solve business problems. You always bring strong critical thinking, collaboration, and problem-solving skills to your work.

Responsibilities

• Data SME/Data Owner- large, complex and/or multiple sources
  • Possess deep knowledge and understanding of your data domain/asset(s). Data domains and assets are large, complex or multiple in nature.
  • Deeply understands and upskills others on the business domain, business context and products that use your data
  • Own connection and relationship back to source stakeholders/vendor (internal and/or external); Define and manage multiple data feeds to our data partners.
  • Advise, alert and resolve data issues and discrepancies to provide support to internal teams using the data.
  • Coach and mentor junior data analysts within and outside of your domain/asset(s)
• Data Discovery
  • Lead collaboration on data discovery for new/existing data (internal, Kroger, 3^rd party, etc.), including data queries/analysis using various tools (e.g. SQL, PySpark, BigQuery, etc.) in partnership with data science team members to determine usability
  • Validate and proactively identify new use cases for existing data
  • Document what the data is, how it can be used, who owns/supports its, how we receive it (examples: data mapping, flow diagrams, data dictionary, business rules, quality checks, etc.). Model and lead other junior data analysts on data documentation best practices.
  • Collaborate with Product Owners/Managers and cross-functional development teams to ensure data needs and changes are articulated in Jira via Stories, Epics, Features
• Data Governance
  • Partner with Kroger/KTD/3^rd Party and 84.51° data governance on data ingestion, changes, impacts, etc., and ensuring plans are in place for adequate testing, quality, reliability, performance, etc., for our 84.51° data domains/assets
  • Partner with 84.51° Enterprise Standards to mature data standards in your data domain/asset
  • Lead and drive establishment of best practices in the data governance space for your domain/asset(s)

Qualifications, Skills and Experience

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