Data Quality Manager at Allianz Global Corporate & Specialty SE

Madrid, Community of Madrid, Spain -

Full Time

Start Date

Immediate

Expiry Date

01 Feb, 26

Salary

0.0

Posted On

03 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Quality Management, Artificial Intelligence, Data Analytics, Data Cleansing, Stakeholder Management, Solvency 2, Agile Scrum, Six Sigma, Project Management, Change Management, Communication Skills, Relationship Management, Data Visualization, Leadership, Process Optimization, Training

Industry

Financial Services

Description

Key responsibilities The Data Quality Manager oversees and guarantees the quality of the Business's data, while ensuring strict compliance with quality criterias in the implementation of Solvency2 with the Risk teams. On this role, you will also ensure the quality of the data assets used for artificial intelligence, as this directly affects the accuracy and reliability of the results. You supervise the smooth running of internal processes and tools, and intervene in the event of anomalies. As a Data Quality Manager, you are in charge of the following responsibilities: Assess data quality to identify and address errors, inconsistencies, duplicates, and missing data. Develop and implement data quality standards, policies, and procedures. Supervise data cleansing activities to ensure accurate and reliable data. Supports Data Owners in the data quality remediation process. Continuously monitor and improve data quality practices through automation and process optimization. Analyze company data practices and identify areas for improvement. Ensure strict adherence to data quality criteria related to Solvency2 regulations. Collaborate with the IT department and business teams on data quality management projects Develop and maintain data dictionaries and data lineage documentation. Generate regular reports on CDE quality performance metrics. Utilize data visualization tools to effectively communicate data quality insights to management and stakeholders. Conduct training sessions to raise employee awareness of data quality best practices. What you bring Multi-Year experience in collaboration with IT or working within IT department. Multi-Year experience in financial planning and IT cost management. Multi-Year experience in IT stakeholer or vendor management role Experience supporting Artificial Intelligence (AI) initiatives by ensuring high-quality, reliable data. Understanding of AI/Data Strategy to align data quality with business goals. Proficiency in data analytics to drive insights and continuous improvement. Training and Experience in a leadership role. Agile Scrum, OPEX, Six Sigma and/or Project Management Professional (PMP) designation. Demonstratable experience in transformation programs; change management trainings. Excellent communication and relationship management skills. Solid understanding of Solvency 2. Understanding of local and regional labour laws and regulations. Fluency in English is required. French would be a great plus. What we offer Our employees play an integral part in our success as a business. We appreciate that each of our employees are unique and have unique needs, ambitions and we enjoy being a part of their journey. We are there to empower and encourage you with your personal and professional development ensuring that you take control by offering a large variety of courses and targeted development programs. All that in a global environment where international mobility and career progression are encouraged. Caring for your health and wellbeing is key priority for us. This is why we build Work Well programs to providing you with peace of mind and give the flexibility in planning and arranging for a better work-life balance. 75044 | Operations | Professional | Allianz Partners | Full-Time | Permanent

Responsibilities

The Data Quality Manager oversees the quality of business data and ensures compliance with Solvency2 regulations. This role involves assessing data quality, developing standards, and collaborating with IT and business teams on data quality management projects.