Senior Data Quality Analyst

2 weeks ago

Chicago, United States 84.51 Full time
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°

SENIOR DATA QUALITY ANALYST P3699

SUMMARY:

Overall this is a Data Subject Matter Expert role, not a Data Analyst role. Responsibilities will include:
  • Advise, alert, and resolve data issues and discrepancies to provide support to internal teams and external clients using the data.
  • Be comfortable working in different technologies, flexing when needed (Azure, Snowflake,Tableau, PowerBI, Grafana, Databricks ,Hadoop, API's)
  • Have strong business and storytelling acumen to understand and support current and future strategy needs
  • Have strong statistical, ETL, and data science acumen and a passion around bringing new methodologies and capabilities to life to solve business problems
  • 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
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., for commercial clients
  • Partner with CIL Data Domain to mature data standards in each data domain/asset
  • Ability to QA data assets to ensure accuracy and identify potential discrepancies
QUALIFICATIONS, SKILLS, AND EXPERIENCE:
  • Bachelor or Master's degree in mathematics, statistics, analytics, data science or related discipline
  • 2+ years developing analytical solutions using advanced statistical methods and machine learning algorithms
  • Proficient in technology stack. Technology stack includes - Azure, Python, Spark, SQL, Snowflake, Databricks,
  • Ability to leverage Python Packages, APIs, and build custom analytical code processes/algorithms.
  • Able to understand cloud architecture, components and services and collaborate with Engineers
  • 2+ years of experience in consulting or professional services
  • 2+ years of experience in extracting insights from large databases, utilizing and creating internal science/data assets to enable actionable solutions and presenting findings and offerings to clients
  • Strong interpersonal, collaboration, communication, and storytelling skills
  • Ability to communicate technical concepts to technical and non-technical audiences
  • Strong analytical, creative problem-solving and decision-making skills
  • Ability to create computationally efficient solutions with a knowledge of package/algorithm development
  • Passionate about data, SL/ML, technical documentation. Understanding of AI algorithms is a plus

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