Lead Data Quality Analyst, Supply Chain

Unclassified - Cincinnati, OH

Full-time - Mid Level

Cincinnati, OH

About the position

The Lead Data Quality Analyst for Supply Chain at 84.51 plays a pivotal role in supporting end-to-end supply chain workstreams, with a particular emphasis on enhancing supply chain and inventory data. This position is designed for individuals who possess a strong business acumen in the Supply Chain and Inventory Replenishment industry. Candidates with familiarity with 84.51 and Kroger's Supply Chain and Operations data assets will find themselves at an advantage. The role is integral to the SCORe (Supply Chain, Operations, and Replenishment) team, focusing on data needs in Inventory Replenishment, Transportation, and warehouse operations. The Lead Data Quality Analyst will be responsible for bringing in new data, diagnosing data issues, and improving data quality across these domains. As a Lead Data Quality Analyst, you will join a cross-functional technical community that includes analysts, data scientists, product owners, program leads, and software engineers. Your expertise in data will empower others to understand and utilize data effectively to solve business problems. The role requires strong critical thinking, collaboration, and problem-solving skills, which are essential for navigating the complexities of data management in a supply chain context. You will be expected to coach and mentor junior data analysts, ensuring that they are equipped with the necessary skills and knowledge to excel in their roles. In addition to your technical responsibilities, you will also engage in data governance, partnering with Kroger, third-party vendors, and internal teams to ensure data quality, reliability, and performance. This includes establishing best practices in data governance and maturing data standards within your domain. Your ability to communicate effectively with both technical and non-technical stakeholders will be crucial in articulating data needs and changes, as well as in documenting data processes and governance practices.

Responsibilities

• Serve as the Data Subject Matter Expert (SME) and Data Owner for large, complex, and multiple data sources.
• Possess deep knowledge and understanding of data domains and assets, and upskill others on the business context and products that utilize this data.
• Own connections and relationships with source stakeholders and vendors, defining and managing multiple data feeds to data partners.
• Advise and resolve data issues and discrepancies to support internal teams using the data.
• Coach and mentor junior data analysts within and outside of your domain.
• Lead collaboration on data discovery for new and existing data, including data queries and analysis using tools like SQL, PySpark, BigQuery, and Databricks.
• Validate and proactively identify new use cases for existing data.
• Document data usage, ownership, and support, including data mapping, flow diagrams, data dictionaries, business rules, and quality checks.
• Collaborate with Product Owners and cross-functional teams to articulate data needs and changes in Jira via Stories, Epics, and Features.
• Partner with Kroger and third-party data governance teams on data ingestion, changes, and impacts, ensuring adequate testing and quality assurance for data domains.
• Lead the establishment of best practices in data governance for your domain.

Requirements

• Bachelor's degree or equivalent experience.
• Minimum 5 years of relevant experience in data management, data architecture, data governance, or related work.
• Experience collaborating with cross-functional partners across data, data science, product, engineering, and architecture.
• Experience working with external partners, vendors, and third parties.
• Strong technical skills in SQL, PySpark, BigQuery, or similar technologies.
• 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 similar technologies.
• Ability to create high-level flow diagrams to facilitate cross-functional conversations regarding data feasibility and usability.
• Proactive and independent problem-solving skills, along with critical thinking and analytical abilities.
• Strong verbal and written communication skills, with the ability to translate between business and technical language.

Nice-to-haves

• Experience with data visualization tools such as Tableau or Power BI.
• Knowledge of machine learning concepts and applications in data analysis.
• Familiarity with Agile methodologies and project management tools.

Benefits

• Flexible hybrid remote/onsite work schedule.
• Relocation assistance to Chicago or Cincinnati if needed.