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Master Data Management Expert

Job in 1000, Amsterdam, North Holland, Netherlands
Listing for: Accenture
Full Time position
Listed on 2026-08-24
Job specializations:
  • IT/Tech
    Data Engineering, Data Warehousing, Database Administrator, Information & Knowledge Management
Salary/Wage Range or Industry Benchmark: 90000 - 130000 EUR Yearly EUR 90000.00 130000.00 YEAR
Job Description & How to Apply Below

ABOUT THE ROLE

We are looking for a seasoned Master Data Management Expert to own the design, implementation, and governance of enterprise-wide master data across our core business domains — customer, product, supplier, and location. You will work at the intersection of data architecture, integration engineering, and governance policy, partnering with domain owners, data stewards, and engineering teams to ensure our master data is trusted, consistent, and actionable across all platforms and systems.

CORE

RESPONSIBILITIES
  • Lead the end-to-end design, build, and operation of MDM solutions covering customer, product, supplier, and reference data domains
  • Architect and configure MDM platforms (Informatica MDM, Reltio, TIBCO EBX, SAP MDG, or equivalent) for survivorship, match-merge, and hierarchy management
  • Define and enforce master data governance policies, ownership models, stewardship workflows, and escalation paths
  • Develop and maintain data integration pipelines connecting source systems, MDM hubs, and downstream consumers using ETL/ELT tooling
  • Design data quality rules, profiling routines, and remediation workflows — ope rationalising DQ metrics and SLAs
  • Collaborate with data architects to embed MDM standards into the enterprise data model and data product catalog
  • Manage entity resolution, deduplication, and golden record construction logic for high-volume, complex data environments
  • Establish and track KPIs for master data quality, completeness, timeliness, and consistency across all domains
  • Lead data stewardship forums, data council inputs, and cross-functional working groups on master data topics
  • Drive continuous improvement of MDM processes, tooling, and workflows in response to business and regulatory change
MDM Platforms & TGooling
  • 2- 5+ years hands-on experience with enterprise MDM platforms — Informatica MDM (Customer 360 / Product 360 / Supplier 360), Reltio Cloud MDM, TIBCO EBX, SAP Master Data Governance, or Semarchy xDM
  • Deep expertise in Informatica MDM Hub configuration: base objects, landing/staging tables, match-merge rules, trust frameworks, state machine workflows, and UI Workbench
  • Experience with Reltio's entity type modeling, attribute configuration, match rules, survivorship policies, and tenant management
  • Working knowledge of at least one additional MDM or PIM platform (Stibo STEP, Akeneo, Profisee, Magnitude MDM)
  • Ability to evaluate, select, and implement MDM tooling aligned to business and architectural requirements
Data Integration & TGooling Engineering
  • Proven experience designing and building data integration pipelines using Informatica Power Center, Informatica IICS (Intelligent Cloud Services), Mule Soft, Azure Data Factory, AWS Glue, or Talend
  • Proficiency in writing and optimising SQL, including complex joins, window functions, and stored procedures across relational databases (SQL Server, Oracle, PostgreSQL)
  • Experience with real-time and event-driven integration patterns using Kafka, MQ, or equivalent messaging platforms to keep MDM hubs in sync
  • Familiarity with REST and SOAP API development for MDM inbound/outbound integration and golden record publication
  • Knowledge of data virtualisation and federated query patterns to expose master data without full replication
  • Experience with cloud-native pipeline tooling (Databricks, dbt, Spark) is a strong advantage
  • Understanding of CDC (change data capture) patterns and their application in keeping master records current
Data Quality
  • Hands‑on experience with data quality tools — Informatica Data Quality (IDQ), Informatica Axon, Collibra DQ, Ataccama, or Great Expectations
  • Ability to define and implement data quality dimensions: completeness, accuracy, consistency, validity, uniqueness, and timeliness
  • Experience profiling large datasets, identifying root‑cause quality issues, and building automated remediation workflows
  • Track record of building data quality scorecards and dashboards tied to business‑meaningful SLAs
  • Knowledge of address validation, name standardisation, and third‑party enrichment services (D&B, Experian, Loqate)
Master Data Governance
  • Deep understanding of data governance frameworks — DAMA‑DMBOK, DCAM, or enterprise‑specific implementations
  • E…
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