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Associate Principal Engineer, Data Engineer (Enterprise Data Architect-Banking Domain) at Nagarro · globalremotely

Company 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!

Job Description

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.