Job Description

Senior Data Architect is responsible for design and integration of data architecture across business solutions, ensuring that every solution aligns with enterprise data standards and supports strategic data initiatives.

The data architect provides hands-on leadership in designing solution data models, integration patterns, and data sharing mechanisms--balancing innovation with control



Primary Responsibilities and Activities

Apply enterprise data principles and standards at the solution level, ensuring consistent data design and interoperability. Document the Data Flows / lineage visualizing the "as-is" data movement across key components of the Data landscape. Contribute in overall modeling standards, guidelines, best practices and approved modeling techniques and approaches. Contribute in governing the creation of all physical and logical data models in the organization. Lead the data architecture stream within solution delivery projects, driving the end-to-end design of data flows, data stores, and integration patterns Participate in due diligence of new software purchases by reviewing all proposed data models contained in packaged or commercially available applications. Serve on data integration, business intelligence and content management competency panels or teams. Serves as a key connector between the Solution Architecture team and the Data Management Office, ensuring data quality, governance, and compliance are embedded early in the solution lifecycle. Ensure, gatekeeper functions are effectively defined and managed to reduce data redundancy and increase accuracy during the Solution lifecycle. Liaise with the data modeling team, data warehouse team and the application owners in understanding the data interface requirements and help the project team developers to resolve issues related with data requirements. Contribute in selection of data management tools, and the development of standards, usage guidelines and procedures for those tools. Work & liaise with various technology and business stakeholders in resolving and escalating issues related with the data solutions and seek their concurrence and approval as per the established process during the SDLC until the solution is deployed. Provide feedback and improvements over the standards, methodologies, processes and best practices to the enterprise architecture team to review and update enterprise architecture standards both at the group and organization level. Provide data architecture support for RFPs, solution proposals, and vendor evaluations as part of the architecture governance process Contribute to continuous improvement of data architecture standards, data modeling templates, and delivery methodologies Partner with data engineering, BI, and analytics teams to ensure seamless pipeline integration and data availability for downstream use cases Work with the Data Quality / Governance teams in understanding areas where data architecture enhancement will assist the overall quality of the Group's data. Educate senior business representatives in best practices for data quality and to work with them to identify realistic goals and data initiatives Stay updated with emerging data technologies/ industry trends and propose innovative solutions to improve Organization's Data Architecture, ensuring the data solutions are robust, scalable and secure.

Requirements:

Minimum 10+ years of overall experience in data architecture, data modeling, and enterprise data integration, within banking or other highly regulated environments. Strong hands-on expertise in Data Modeling (conceptual, logical & physical) using industry standard tools like Erwin etc. Excellent analytical, problem-solving, and communication skills to effectively translate Business/functional concepts to technical concepts and collaborate with diverse teams A Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field * Strong working knowledge of Data Architecture and Architecture governance frameworks such as DAMA-DMBOK, TOGAF (data domain), and enterprise data modeling standards, with hands-on experience applying these frameworks within the SDLC will be an added advantage