Data Architect

Data Architect / London 1 day per week on client site (Canary Wharf) / 12 months / Start ASAPOur client provides audit, risk, finance and compliance solutions that help financial organizations improve efficiency and effectiveness across their enterprise.The position is for the customer's business unit, which develops a solution for commercial banks across the world to automate their reporting, as required by banking regulatory legislation.Key stakeholders are located in London. So the candidate is expected to be from London or with a possibility of business trips.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. 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.Key Responsibilities:Data Architecture & Design:-Develop and implement a robust data architecture strategy that supports the organisation’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.Data Engineering Pipelines:- 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.• Data Lineage & Governance:- 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.Banking Risk & Regulatory Reporting:-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.Collaboration & Leadership:- 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.Qualifications:Education:- Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field.Experience:-Minimum of 8 years of 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, Open Lineage)and data governance frameworks.- In-depth knowledge of banking risk management and regulatory reporting frameworks (e.g., Basel III/IV, CRR/CRD).Technical Skills:-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.Soft Skills:- 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.Preferred Qualifications:• Certification in data management or architecture (e.g., CDMP, TOGAF).• Experience with machine learning and AI-driven data processing.• Knowledge of additional financial regulations and reporting standards