Job Description

Overview

We are seeking a highly detail-oriented Data Steward to play a critical role in maintaining the accuracy, consistency, and integrity of core organizational data. This position owns the governance, quality, and lifecycle of key master data—including customer, product, and operational datasets—ensuring reliable information is available across systems for reporting, analytics, and decision-making. The Data Steward collaborates cross-functionally, leads data quality initiatives, and supports the organization in driving clean, trustworthy, and accessible data.

This is a 100% remote role .

Essential Job Duties

• Maintain and ensure the accuracy and consistency of customer, product, and operational data across multiple systems.
• Implement and manage data governance policies, standards, and procedures to support data integrity and compliance.
• Partner with IT and business teams to develop and enhance data models that strengthen reporting and analytics capabilities.
• Conduct regular data quality audits to identify discrepancies, resolve issues, and uphold data standards.
• Facilitate the creation and maintenance of master data records using consistent taxonomy and established protocols.
• Develop and deliver training to end-users on master data management best practices, processes, and data entry requirements.
• Lead cross-functional initiatives to consolidate, clean, standardize, and optimize master data enterprise-wide.
• Design and build custom reports and dashboards for stakeholders to monitor data quality, status, and trends.

Key Skills

Data Governance: Ability to implement and enforce policies that ensure data accuracy, consistency, and security across the organization.

Data Quality Management: Skilled in auditing, monitoring, and correcting data to maintain accuracy, reliability, and completeness.

Master Data Integration: Experience consolidating data from multiple systems into a unified and accessible source of truth.

Metadata Management: Ability to categorize, structure, and tag data for efficient retrieval, governance, and analysis.

Data Lifecycle Management: Understanding of data creation, storage, archiving, and retirement to ensure appropriate access and compliance.

Data Modeling: Ability to design structured representations of data systems, define relationships, ensure integrity, and support business objectives.

Experience Requirements

• Extreme attention to detail and a passion for maintaining clean, reliable data.
• Expert-level Excel skills and comfort working with large, complex datasets.
• Ability to write clear, concise documentation for all master data elements and processes.
• Strong communication skills with the ability to collaborate effectively across teams and departments.
• Industry experience preferred but not required.

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