Data Architect, Wolters Kluwer

• The ideal candidate will possess a deep understanding of data architecture principles and have hands-on experience in the financial services industry, particularly in risk management and regulatory compliance
• Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field
• Extensive experience in data architecture, data engineering, or a related role, with a strong background in financial services
• Proven experience in designing and implementing data engineering pipelines and data architectures at scale
• Hands-on experience with data lineage tools (e.g., Apache Atlas, OpenLineage) and data governance frameworks
• In-depth knowledge of banking risk management and regulatory reporting frameworks (e.g., Basel III/IV, CRR/CRD)
• Proficiency in data engineering tools and technologies such as Apache Airflow, Spark, Kafka, Hadoop, or similar
• Strong SQL skills and experience with relational and NoSQL databases
• Experience with cloud platforms (AWS, Azure, GCP) and data warehousing solutions (e.g., Snowflake, BigQuery)
• Familiarity with data modeling tools and techniques, as well as metadata management solutions
• Excellent communication and collaboration skills, with the ability to work effectively across teams
• Strong problem-solving skills and the ability to think strategically about data solutions
• Leadership experience with a proven ability to mentor and develop talent

Desirable

• We are seeking an experienced Data Architect to lead the design, development, and implementation of our data architecture, with a strong emphasis on data engineering pipelines, data lineage, data governance, and banking risk or regulatory reporting
• Develop and implement a robust data architecture strategy that supports the organization’s data needs, focusing on scalability, security, and performance
• Design and optimize data models, schemas, and data flow diagrams to meet business requirements, ensuring alignment with best practices in data engineering and architecture
• Lead the design, development, and maintenance of data engineering pipelines to support ETL/ELT processes, data integration, and data transformation
• Implement automated data pipelines using tools like Apache Airflow, Spark, Kafka, or similar technologies, ensuring data is processed efficiently and accurately
• Establish and maintain comprehensive data lineage tracking across all data assets, ensuring transparency and traceability from source to destination
• Develop and enforce data governance policies, including data quality standards, metadata management, and access controls, to ensure data integrity and compliance
• Collaborate with cross-functional teams to define and implement data stewardship practices
• Design data solutions that meet the stringent requirements of banking risk management, including credit risk, market risk, and operational risk
• Ensure that the data architecture supports regulatory reporting requirements, such as Basel III/IV, CRR/CRD, and other relevant banking regulations
• Work closely with risk management teams to understand their data needs and deliver solutions that enable accurate and timely reporting
• Collaborate with product and business teams to ensure alignment between data architecture and business objectives
• Provide technical leadership and mentorship to junior data engineers and architects, fostering a culture of continuous learning and improvement
• Stay up-to-date with industry trends, emerging technologies, and best practices in data architecture and financial services