Data Quality Expert (f/m/d)

In this hybrid Data Quality Expert role, you will shape and operate data quality tooling and metadata management within AllianzGI’s data platform. You’ll work across data products, engineering, and business stakeholders to improve data quality across pipelines, dashboards, and governance processes. The role combines Databricks development with DQI/DQX platform responsibilities and dashboard stewardship, offering hands-on impact at scale. You will partner with teams to onboard sources, define checks, and monitor quality KPIs to enable trusted data for decisions.

• flexible work arrangements
• pension/savings plans
• relocation/childcare support
• company share purchasing plan
• mental health and wellbeing programs
• learning & development opportunities

• Develop and operate the DQI data product for metadata storage, standardisation, and visualization
• Build and optimize pipelines for metadata load interfaces across data quality platforms
• Onboard new metadata sources; conduct business analysis and technical evaluation of datasets
• Maintain DQI platform and data quality checks lifecycle; monitor KPIs and resolve failures
• Enhance the enterprise data quality tooling (DQX) and implement new attributes/features per business needs
• Develop and maintain data quality dashboards and reporting in alignment with stakeholders
• Coordinate platform upgrades, testing, and production releases with minimal disruption
• Manage user access, environments, schedules, and configurations for the DQI platform
• Ensure governance alignment with enterprise data strategy and regulatory requirements
• Maintain integration with additional DQ platforms and provide training/support to data products and functions

• Databricks development experience (pipelines, notebooks, jobs)
• Familiarity with the DQX framework or similar data quality rule frameworks
• Strong business analysis skills to translate DQ requirements into technical specs
• Stakeholder management across Data Products, business functions, and platform teams
• Knowledge of or willingness to learn Microsoft Power BI
• Root-cause analysis for DQ findings and pipeline incidents
• Experience with data modelling and metadata management best practices
• Understanding of DQ operations: check lifecycle, KPI monitoring, continuous improvement
• Experience with Agile methodologies
• Knowledge of AI/Data Strategy, Data Cleaning, and Data Governance is desirable

• Stakeholder management
• Analytical thinking
• Cross-functional collaboration
• Databricks development (pipelines, notebooks, jobs)
• DQX or equivalent data quality rule framework
• Power BI familiarity