Lead Data Quality Analyst, Supply Chain Specialist

84.51° Overview:

84.51° is a retail data science, insights and media company. We help The Kroger Co., consumer packaged goods companies, agencies, publishers and affiliates create more personalized and valuable experiences for shoppers across the path to purchase.

Powered by cutting-edge science, we utilize first-party retail data from more than 62 million U.S. households sourced through the Kroger Plus loyalty card program to fuel a more customer-centric journey using 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

LEAD DATA QUALITY ANALYST, SCORe SUPPLY CHAIN (P4018)

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, 3rd 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/3rd 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

Qualifications & Experience

Skills

Bachelor's degree or equivalent experience

Experience collaborating with cross-functional partners across data, data science, product, engineering, architecture

Experience collaborating with external partners, external vendors, third parties

Minimum 5 years of relevant experience in data management, data architecture, data governance or related work

Strong technical skills using SQL, PySpark, BigQuery or similar

Technical understanding of data, flow diagrams, and ability to read and write code and scripts

Familiarity with Hadoop, Github, Jira, Cloud (Azure), Oracle, Snowflake, Confluence or other similar technologies

Ability to create high level flow diagrams to facilitate cross-functional conversations, in order to validate the feasibility and usability of data

Proactive and independent problem solving, critical thinking and analytical skills

Verbal and written communication skills, ability to translate between business and technical and liaise with various stakeholders

Strong mentor and coach to junior talent.

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