Data Management Associate

About us: Billigence is a boutique data consultancy with global outreach and clientele, transforming the way organisations work with data. We leverage proven, cutting-edge technologies to design, tailor, and implement advanced Business Intelligence solutions across Cloud Data Warehousing, Visualisation, Data Science, Data Engineering, and Data Governance. Headquartered in Sydney, Australia, with offices around the world, we help clients navigate complex business challenges, eliminate inefficiencies, and enable scalable, data-driven decision-making. About the Role: We are looking for experienced Data Management Associates / Data Business Analysts to join a major client engagement supporting an enterprise Master Data Management and Data Enablement programme. This is a fully remote position. You will join a dedicated Data Enablement function whose remit is to make trusted, well-governed and well-documented data available across the business. The role sits between the technical teams building data pipelines and the business teams consuming the outputs — hands-on with the data itself while owning the documentation, standards and metadata that let colleagues understand and rely on it. This is a delivery-focused, individual contributor role with genuine ownership of data quality and stewardship across a set of assigned data domains. What You'll Do: Gather, analyse and document business, functional and data requirements through stakeholder workshops, interviews and collaborative sessions. Profile and analyse datasets to identify data quality issues — duplication, completeness, consistency and integrity gaps — and carry out root-cause analysis. Define and run validation and completeness checks, tracking data quality against agreed metrics and thresholds. Coordinate the resolution of data issues with source-system and engineering teams, cleansing, de-duplicating and reconciling records where required. Support the maintenance of master and reference data, applying agreed standards for key entities so data is consistent and comparable across systems. Act as domain data steward — the point of contact for what the data means, where it comes from and how it should be used. Maintain the data catalogue and business glossary, keeping definitions, ownership and business context accurate and current. Document data lineage and flows across source systems, stores and reporting layers so they are transparent and auditable. Produce data dictionaries, standards, process notes and how-to guides to a consistent, reusable standard. Contribute to data quality reporting, producing regular views of data health and recommending improvements to controls and processes. Apply and help enforce data governance policies covering access, retention, classification and privacy, flagging risks and supporting audit requirements. Partner with engineering, product, BI and business teams to embed quality and governance requirements early in delivery. Support and mentor data stewards, sharing knowledge and raising data literacy across teams. What You'll Need: Solid experience (typically 2–4 years) in a data management, data quality, data governance, data analysis or data operations role. Experience delivering large-scale data management initiatives across a complex data landscape. Demonstrable experience improving data quality — profiling, cleansing, reconciliation and root-cause analysis. Solid understanding of data governance concepts: stewardship, master and reference data, metadata, lineage, classification and data privacy including GDPR. Strong requirements gathering and workshop facilitation skills, with the ability to translate business needs into clear, traceable documentation. Confident working with spreadsheets and data at scale, with a meticulous eye for accuracy and detail. Clear written and verbal communication — able to document data clearly and explain it to both technical and non-technical audiences. A collaborative, proactive approach and the ability to manage several workstreams independently. Desirable: Experience with data catalogue, data quality or governance tooling — Collibra, Alation, Informatica, Microsoft Purview or similar. Familiarity with modern data platforms and pipelines — cloud data warehouses, dbt, ETL/ELT tooling. Exposure to BI and reporting tools such as Power BI, Tableau or Looker, and to supporting self-service analytics. AI fluency — both using AI tools and enabling accurate, trustworthy data assets for AI use cases. Scripting for data tasks, for example Python. Experience of data management within a regulated industry. A relevant degree or professional data qualification such as DAMA / CDMP. Got an y questions? Get in touch — we're happy to talk the role through in confidence.