Associate Principal Engineer, Data Engineer (Enterprise Data Architect-Banking Domain)

Job description

👋🏼**We're Nagarro.** We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (18,500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! REQUIREMENTS: - Total Experience 11+ years - Strong experience in Data Architecture, Enterprise Architecture, or Data Engineering. - Proven experience defining and delivering enterprise data architecture strategies, target states, and architectural roadmaps. - Strong experience establishing and governing enterprise data architecture practices, including governance forums, operating models, and Terms of Reference (ToRs). - Experience creating enterprise data flows across business domains, including current state, transition state, and target state architectures. - Strong ability to review data architecture deliverables and ensure compliance with enterprise standards, policies, and governance principles. - Hands-on experience with enterprise data modelling and industry-standard data models such as **FSLDM (Financial Services Logical Data Model)**, **BIRD (Banks' Integrated Reporting Dictionary)**, or equivalent. - Strong understanding of modern data architecture paradigms, including, Data Lake, Data Mesh, Data Fabric, Hybrid Data Architecture, Agentic Data Architecture - Strong understanding of enterprise data governance, metadata management, data quality, lineage, and master data management concepts. - Experience collaborating with enterprise architects, business stakeholders, engineering teams, and governance bodies to deliver scalable data solutions. - Excellent analytical, problem-solving, and decision-making skills. - Strong communication, stakeholder management, and leadership capabilities. - Experience working in Agile delivery environments. - Experience designing enterprise-wide logical and conceptual data models. - Experience evaluating, selecting, and recommending enterprise data architecture and modelling tools. - Hands-on experience with modern cloud data platforms such as **Databricks**, **Snowflake**, or similar technologies. - Familiarity with enterprise data governance platforms such as **Collibra**. - Experience with Enterprise Architecture tools such as **LeanIX**, **Ardoq**, or equivalent platforms. - Experience working in regulated industries such as Banking, Financial Services, or Insurance is an advantage. RESPONSIBILITIES: - Define and drive the enterprise data architecture strategy, principles, standards, and target-state architecture. - Develop enterprise data architecture roadmaps and transition plans aligned with business and technology strategies. - Establish and lead enterprise data governance forums, architecture review boards, and decision-making processes. - Create and maintain enterprise data architecture artifacts, including conceptual, logical, and physical data models, data flows, and architecture blueprints. - Design enterprise data flows across business domains and ensure alignment with target-state architecture. - Review and approve data architecture deliverables, ensuring compliance with enterprise standards, governance policies, and best practices. - Collaborate with business, engineering, analytics, and architecture teams to design scalable and reusable data solutions. - Evaluate emerging data technologies, architecture patterns, and tools, providing recommendations aligned with organizational objectives. - Provide architectural guidance for cloud data platforms, including Databricks, Snowflake, and other modern data ecosystems. - Define and promote best practices for data modelling, metadata management, data quality, lineage, and governance. - Support enterprise transformation initiatives by ensuring consistency, interoperability, and scalability across the organization's data landscape. - Mentor architects and engineering teams on enterprise data architecture principles and governance practices. - Stay current with evolving data architecture methodologies, industry standards, and emerging technologies, driving continuous improvement across the enterprise. Bachelor’s or master’s degree in computer science, Information Technology, or a related field.