Full-Time

Lead Data Analyst

P2172

Posted on 3/27/2023

84.51 Degrees

84.51 Degrees

1,001-5,000 employees

Retail data science for personalized shopper experiences

Data & Analytics
Consumer Goods

Senior

Northbrook, IL, USA + 5 more

Required Skills
Microsoft Azure
Data Science
Git
BigQuery
SQL
JIRA
Hadoop
Confluence
Oracle
Data Analysis
Snowflake
Requirements
  • 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
  • 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
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

84.51° stands out as an excellent workplace due to its focus on leveraging advanced science and first-party retail data to deliver personalized shopper experiences. This retail data science company is deeply embedded in understanding consumer behavior, which puts it at the forefront of the industry in terms of both knowledge and technology. Such a dynamic and technically sophisticated environment provides a stimulating workplace for professionals looking to advance in data science and retail marketing.

Company Stage

M&A

Total Funding

$5.5M

Headquarters

Cincinnati, Ohio

Founded

2015

Growth & Insights
Headcount

6 month growth

0%

1 year growth

6%

2 year growth

25%
INACTIVE