Data Quality Manager

Schelle , Flanders, Belgium

Type: n/a

Category: IT & Internet & Media

Requirements: English
Company: Tosca
Region: Schelle , Flanders

ABOUT TOSCA

Tosca is a global leader in reusable packaging and pooling solutions that service the supply chain end to end. Re-use is the key word as Tosca facilitates moving away from single use packaging towards a circular model of reusable packaging with its robust portfolio of plastic containers, pallets, bins, crates and more. We focus on optimizing the flow of perishables, eliminating waste at every turn product, packaging, labor and transportation waste. Our reusable plastic products improve the quality of product delivered, create more efficient supply chains, and are more sustainable than single-use packaging.

We are seeking a highly motivated and detail-oriented Data Quality Manager for our office in Schelle (Belgium).

Position Purpose

The Data Quality Manager - EMEA is responsible for establishing, maintaining, and improving data quality across their assigned region. This role works closely with Data Stewards and operates at the intersection of Applications, Data Engineering, BI Development, and Business Operations, offering a unique vantage point to identify and address data quality issues. Active participation in BI Development and Data Engineering projects is essential to stay aligned with evolving processes and proactively detect potential data quality risks. A key responsibility is facilitating the enforcement of Data Governance rules by leading the design, distribution, and training on data quality metrics for all stakeholders involved in the data lifecycle.

Responsibilities

Data Quality Management

Execute and operationalize data management competencies within the organization, specifically for data housed in the DWH (Snowflake & Redshift). This includes, but is not limited to, data quality assurance, metadata management, master data management, data modeling, and the implementation of data standards and data strategy as defined by the Global Data Architect. While the BI&A team is responsible for data within Snowflake, extensive coordination with application owners and data stewards will be required to ensure alignment with enterprise data governance initiatives.

• Lead the implementation of data governance frameworks, ensuring alignment with Toscas strategic goals of treating data as an asset.
• Partner with Data Stewards to identify and resolve data quality issues and ensure adherence to data governance best practices.
• Be the point person on cataloguing data quality issues from all parts of the organization and prioritize based on ROI.
• Collaborate with the Data Engineering team on the setup and operationalization of the SODA data quality platform.
• Regularly provide Data Quality metrics to stakeholders to create actionable feedback and an objective measure for leaders across the organization to hold people accountable, through all stages of the data lifecycle.
• Develop training materials and conduct workshops to enhance data literacy and promote data quality awareness across the organization.

BI Development & Special Projects

Act as a bridge between Data Engineering & BI Development, sometimes leading, sometimes following, requiring extensive collaboration with the BI Operations Manager EMEA.

• Responsible for in-report documentation, inclusive of but not limited to data lineage & Data Quality scoring.
• Collaborate with the BI team, including but not limited to the following;

Act as a BI Developer when necessary, supporting projects requiring additional expertise or bandwidth.

Lead or contribute to special BI projects that align with organizational goals.

Data Engineering/Architecture Support

At the direction of the Global Data Architect, collaborate with the Data Engineering team to ensure data structures support BI&A needs, including but not limited to the following:

• Data profiling, exploratory analysis, and data modeling to identify patterns, inconsistencies, or gaps
• Creating class diagrams for major applications, flow charts, ERD, and data lifecycle diagrams.
• Developing data dissemination diagrams to map data flows and dependencies.
• Creating and maintaining an Application/Data matrix to document the relationships between applications and their associated data.
• Cataloging and monitoring key data assets deemed essential to the organizations operations.
• Creating and maintaining Data Dictionaries to document metadata, definitions, and standards for improved data consistency and governance.
• Ad-hoc Data

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