Senior Data Steward, Re:Cycle Reverse Logistics, Re:Cycle Reverse Logistics

Amazon.com; Dublin; Presencial; EUR 60.000 - 90.000; Jornada completa

Descripción de la vacante

Amazon Web Services (AWS) seeks a detail-oriented Data Steward for re:Cycle Reverse Logistics Ireland. You will drive data integrity across multiple warehouse systems, implement SQL audits, and manage data quality metrics for global operations with millions of monthly transactions.

The role emphasizes root-cause analysis, governance strategy development, and collaboration with engineering and vendors to ensure reliable, actionable data for planning and performance reviews.

Formación

• Experience auditing and analyzing system data to identify discrepancies and improve accuracy.
• Familiarity with data governance and data quality principles in large data environments.
• Ability to design, implement, and monitor data-quality metrics and scorecards.

Responsabilidades

• Own accuracy, consistency, and completeness of source of truth data across warehouse systems.
• Design and maintain SQL-based audit mechanisms to validate data between sources and downstream warehouse.
• Root cause data discrepancies, triage incidents by impact, and drive resolution with providers and engineers.
• Define and track data quality health metrics; develop scorecards and system health reports.
• Develop data standards, policies, and governance strategies; prove policy compliance.
• Identify reporting gaps; collaborate with data engineering to influence architecture and data.
• Validate data accuracy in staging environments ahead of production releases with vendors.

Conocimientos

Data stewardship

SQL

Data quality

Data governance

Root cause analysis

Stakeholder communication

Metrics reporting

Descripción del empleo

Data Steward, Re:Cycle Reverse Logistics

Job ID: 10581611 | Re:Cycle Reverse Logistics Ireland Limited

The re:Cycle Reverse Logistics Operations team offers worldwide cloud computing providers with a centralized means to disassemble, sort, function test, in-warranty return, repair, erase/wipe, and disposition server and networking assets that break or are no longer needed in the fleet. The team is seeking a detail-oriented, analytical, and self-driven Data Steward to support its global operations by driving and working collaboratively across teams to maintain data consistency and accuracy, and by generating and driving data-related performance metrics in the organization’s warehouse management system. This scope will ensure data reliability for the organization’s three operating systems, driven by 400+ global users through our four global facilities that are generating millions of transactions per month across 70+ data tables. This role is critical to the re:Cycle Reverse Logsitics system-management team that is responsible for maintaining application security, data, and compliance, and plays a key role in enabling global operations with reliable information needed to align on daily, monthly, and annual plans, and tracking operational performance to plan. Auditing and analyzing the system’s data (both extracted and in-application), repairing inaccurate data, working across the organization and 3P service provider 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.

Key job responsibilities

• Own accuracy, consistency, and completeness of source of truth data across the organization's warehouse management systems.
• Design and maintain recurring SQL based audit mechanisms that validate data accuracy between source systems and the downstream data warehouse
• Root cause data discrepancies, triage and prioritize incidents by business impact, and drive resolution through the system's 3P service provider and internal engineering.
• Define and track data quality health metrics; develop scorecards and system health reports for stakeholders and QBRs.
• Develop, formalize, and communicate data standards, policies, and governance strategies; prove compliance against those policies.
• Identify reporting gaps between source and downstream systems; collaborate with data engineering to influence architecture, automate risk identification, and enable new system data.
• Validate data accuracy in staging environments ahead of production release in collaboration with Vendor Product Managers.

A day in the life

About AWS

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