Senior Data Solutions Analyst (P2206, P4376)

As a Senior Data Solutions 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.  

The Senior Data Solutions Analyst will serve as a subject matter expert in data management and solutions, focusing on data stewardship, querying, and strategic use. This role requires a deep understanding of the organization's data assets, the ability to craft solutions that optimize data usage, and the capability to communicate insights and recommendations to stakeholders effectively.   

Responsibilities 

• Be comfortable working in different technologies, flexing when needed (Azure, Snowflake, Databricks, Hadoop, API's, Tableau, PowerBI, Grafana) 

• Have strong business and storytelling acumen to understand and support current and future strategy needs. 

• Enjoy working in an exploratory role with the ability to drive for results in ambiguity. 

• Be comfortable thinking outside the box or creatively problem solving. 

Data SME/Data Owner  

• Own connection and relationship back to data source stakeholders/vendor (internal and/or external). 

• Possess deep knowledge and understanding of your data assets and domain.  

• Advise, alert and resolve data issues and discrepancies to provide support to internal teams and external clients using the data.    

• Develop deep understanding of the business domain, business context and products that use your data. 

• Identify opportunities for process improvement and innovation in data management practices. 

Data Discovery  

• Collaborate 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.  

• Document data assets, how they are used, who owns/supports asset, and ETL processes (examples: data mapping, flow diagrams, data dictionary, business rules, quality checks, etc.)  

• Create data publishing requirements to inform engineering partners. 

• Validate and recommend new use cases for existing data.  

• 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 upstream data owners on data ingestion, changes, impacts, etc., and ensuring plans and communications are in place for adequate testing, quality, reliability, performance, etc. 

• Establish and enforce data governance policies and procedures to ensure data integrity and compliance. 

• Monitor data quality metrics and address issues to maintain high standards of data accuracy. 

QUALIFICATIONS, SKILLS, AND EXPERIENCE: 

• Bachelor’s or master’s degree in information management, analytics, data science, mathematics, statistics, business administration, or related discipline. 

• 2+ years proven experience in data analysis, management, or stewardship roles working with large datasets. 

• Proficient in technology stack. Technology stack includes – Azure, SQL, Snowflake, Databricks, PySpark. 

• Strong analytical, creative problem-solving and decision-making skills. 

• Strong interpersonal, collaboration, communication, and storytelling skills. 

• Ability to communicate technical concepts to technical and non-technical audiences. 

• Able to understand cloud architecture, components and services and collaborate with Engineers. 

• Passionate about data and technical documentation.  

• Supply Chain data experience is a plus. 

• Understanding of AI algorithms is a plus. 

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