Data Steward

We are looking for data stewardship support in building customer domain data products to enable a Data Mesh approach. The focus is on data quality management, governance frameworks, metadata, and stakeholder enablement. This role drives adoption of data governance standards, ensures discoverability and clear data definitions, and works closely with product and engineering teams to improve data reliability and usability.

Scope of Services

The consultant will support the organisation by:

• Defining and maintaining data quality rules, tests, and dashboards (using dbt / Elementary)
• Leading root-cause analysis for data quality issues and following up on corrective actions
• Maintaining business definitions, harmonisation rules, and metadata across datasets
• Reviewing data models, data contracts, and data mappings to ensure alignment with governance standards
• Presenting data quality and governance insights to stakeholders
• Advocating the data mesh concept and data-as-a-product principles
• Collaborating closely with data engineers, data stewards, software engineers, and product teams

• Strong SQL skills and experience with dbt for writing and evaluating data quality tests
• Experience with data visualisation tools (Looker Studio, Power BI)
• Hands-on experience with data quality frameworks: defining rules, writing tests, and investigating failures
• Solid understanding of data models, databases, data warehousing, and data flows
• Experience with customer data (profiles, purchases, interactions) is a strong plus
• Knowledge of data governance frameworks, metadata management, and data cataloguing best practices
• Python and/or regex is a plus
• Experience with cloud environments, ideally GCP

Communication & Collaboration

• Strong collaboration skills with Data Management Leads, Product Owners, Data Engineers, and Software Engineers
• Ability to present insights clearly using dashboards, Miro, and similar tools
• Structured problem-solving mindset to identify issues, owners, and drive resolution
• Ability to translate business requirements into data quality rules and governance standards
• Proactive mindset - comfortable working in an evolving environment

Most Important

• Data quality definition and implementation (SQL, dbt)
• Knowledge of data governance frameworks and best practices
• Strong analytical problem-solving skills
• Stakeholder collaboration and enablement