Lead Data Analyst (P2172)

84.51° Overview:

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

Powered by cutting edge science, we leverage 1st party retail data from nearly 1 of 2 US households and 2BN+ transactions to fuel a more customer-centric journey utilizing 84.51° Insights, 84.51° Loyalty Marketing and our retail media advertising solution, Kroger Precision Marketing.

Join us at 84.51°!

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LEAD DATA ANALYST, DATA DISCOVERABILITY

LOCATION: FLEXIBLE (*IN THE US ONLY) 

Summary 

Data Discoverability is a cross-functional and joint 84.51°- KTD collaborative team within Enterprise Capabilities that is making all data assets discoverable across both 84.51° and Kroger. The team is focused on defining a standard structure and means of cataloging our data so that it is accessible and understandable to data consumers. We are looking for a someone who first and foremost is passionate about data. The data analyst understands the need for data literacy and has a passion for building out content around data to enable and communicate with users. This analyst should understand the upstream and downstream nature of data work and its complex systems. Soft skills that lend to sales engineering and enabling through empathy and collaboration, and understanding of data governance, data compliance, and data quality would be a plus to assist in enabling these processes long term.

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)
  • 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)
• Data Discoverability
  • Collaborate with team to research, design, and implement Enterprise Data Catalog elements using industry knowledge, experience and stakeholder use cases.
  • Strategize with team, trusted partners, and stakeholders to define data standards, guidance, training, policies, etc.
  • Facilitate onboarding of new data assets and use cases into Enterprise Data Catalog
  • Model and coach junior data analysts and users on best practices and data asset registration

Qualifications & Experience

• Bachelor's degree or equivalent experience
• Experience with complex data domains, systems, and processes
• 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

Skills

• 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 APIs, Hadoop, Github, Jira, Cloud (Azure), Oracle, Snowflake, Confluence or other similar technologies
• Knowledge of Data Lineage, Data Quality, Data Governance and Compliance concepts
• 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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