Amazon Data Steward Cycle Reverse Logistics 

United States, Pennsylvania 

249508503

Key job responsibilities
•Ensuring accuracy, consistency, and completeness of system data, both within and outside of the application
•Developing and enforcing data standards, policies, procedures, and governance strategies to maintain global data integrity and compliance
•Performing regular data quality assessments, developing and implementing scorecards and improvement plans to address identified issues
•Working closely with stakeholders across the organization and service providers to understand data requirements and to root cause/repair data issues
•Utilizing SQL to query, extract, and analyze data to support business needs
•Generating and presenting data performance metrics and reports/visuals to leadership to drive data consistency and accuracy
•Providing training and support to team members on data-related topics and best practices
•Managing ticket queue, prioritization, and tradeoffs for strategic system developments
•Facilitating migration of legacy data into new systems and reporting architecture as neededA day in the life
Auditing and analyzing the system’s data (both extracted and in-application), repairing inaccurate data, working across the organization and 3P service providers to root cause and repair recurring data issues, analyzing and prioritizing data "bugs" for resolution, supporting data change management initiatives, and generating/driving data-related performance metrics for leadership presentation are all in a day’s work for the reverse logistics Data Steward.

•3+ years of data management, data engineering, or related experience in a warehousing, supply chain, manufacturing, or reverse logistics environment
•Bachelor’s degree in Data Science, Computer Science, Information Systems, or related, or 4+ additional years of related experience in lieu of a degree
•2+ years using Microsoft Office tools (Excel, Word, etc.)

•Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
•Experience with data modeling, warehousing, and building ETL pipelines using AWS cloud tools
•Experience using data visualization tools (Tableau, Quicksite, etc.) in developing insightful dashboards to share data with a variety of stakeholders
•Strong analytical and problem-solving capabilities with a keen eye for details
•Proven track record for improving metrics and performance to SLA
•Strong verbal and written communication skills to translate complex problems using non-technical terms
•Experience managing a 3rd party vendor