Business Data Steward

Business Data Steward provide consistent, hands-on stewardship for data products across data domains. Translates consumer needs into data product requirements, supports each product through its lifecycle from onboarding to retirement, and makes sure the quality, metadata, lineage and access requirements attached to a product are defined, documented , and available for adoption. Key accountabilities 1. Consistent stewardship across data domains Apply the agreed stewardship support model consistently across assigned domains, adapting to domain context without diverging from the standard. Contribute to defining and refining the support model with data domain leads and the accountable stewardship leads. Identify and escalate inconsistencies, capacity gaps and cross-domain conflicts via the established data governance process . 2. Product requirements and downstream consumer needs Engage consumers to elicit what each data product must deliver: attributes, definitions, transformation logic, refresh expectations and fitness-for-purpose. Translate business needs into requirements that product and Tech teams can build against, at the level of detail the delivery cadence requires. Document upstream and downstream dependencies for products in scope, so the impact of a change is known before it is made. Confirm requirements with consumers and record acceptance criteria and expected data quality. Keep requirements current as needs evolve , and route material scope changes to the accountable lead. Collaborate with Tech partners during data product development phase. Perform UAT testing of authoritative data products. 3. Lifecycle support Onboarding — support the intake of new data products, ensuring requirements, ownership and documentation & required approvals ( i.e. IHD data use/re-use) are in place before build . Change — assess incoming change requests for downstream impact, record them, and track them through to implementation. Reuse — check whether an existing product already meets a new need before a new one is commissioned. Rationalization — identify duplication, redundancy and near-identical products, and recommend consolidation. Retirement — support decommissioning of superseded products, confirming that replacements are live, validated and accepted first. Handover — complete agreed product-support handovers, leaving receiving teams able to operate the product without ongoing dependency. 4. Quality, metadata, lineage and access Define the data quality expectations and checks that apply to each product in scope, with the accountable stewardship leads. Ensure required metadata is captured and maintained in the agreed tooling — definitions, ownership, source, transformation logic and authoritative-source status. Document lineage from source through to consumption at the level of detail agreed for the product. Skills and experience Essential Experience in data stewardship, data governance, business analysis or data product ownership. Able to elicit requirements from business users and express them precisely enough to build against — including attribute-level definitions and transformation logic. Working knowledge of data quality concepts and how checks are specified and applied. Familiarity with metadata management and data cataloguing tooling. Comfortable reading data models and source-to-target mappings, and working with detail at that level. Strong documentation discipline — keeps records current, versioned and traceable. Desirable Experience stewarding data across more than one data domain. Experience of rationalizing or decommissioning legacy data assets. Experience working to an agile delivery cadence alongside product and engineering teams. Familiarity with data lineage tooling and access request and approval processes. Exposure to a regulated data environment. U nder stand ing the Data Mes h con cept ( for in ter nal candidate s: understa nding t he DD F pri ncip les ) . Expe rience in syste ms , li ke: D enodo, Snow fla ke, Data bricks, C ollibr a . </