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Associate Principal Engineer, Data Engineer – Enterprise Data Architecture, Banking
NagarroAssociate Principal Engineer designing and delivering enterprise data architecture strategies for banking. Collaboration with stakeholders and governance functions for data initiatives and platforms.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in defining and implementing enterprise data architecture principles and governance frameworks, ensuring alignment with business strategies and compliance with industry standards. Proficient in designing scalable data solutions and leading strategic data initiatives across multiple business domains.
Highest-signal resume keywords
Enterprise Data Architecture DesignData Governance Framework DevelopmentData Modelling MethodologiesCloud Data Platforms (Databricks, Snowflake)Stakeholder Management
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Enterprise Data ArchitectureData Flow DesignData Integration ArchitectureData ModellingData GovernanceData LakeData MeshData FabricHybrid ArchitecturesAI-Enabled Data Ecosystems
Soft Skills
CommunicationFacilitationDecision-MakingAnalytical SkillsProblem-Solving
Tools & Technologies
CollibraLeanIXArdoqEnterprise Architecture ToolsMetadata Management Platforms
Industry Keywords
Financial ServicesBankingRegulated IndustriesGovernance StandardsBest Practices
Tech Stack
Tools & technologiesCloud
About the role
Key responsibilities & impact- Define, implement, and maintain enterprise data architecture principles, standards, policies, and target-state architectures aligned with business and technology strategies.
- Design and govern current-state, transition-state, and target-state data architectures and data flows across multiple business domains.
- Develop and maintain enterprise data models, ensuring alignment with industry standards and organizational data architecture principles.
- Review and approve data architecture artefacts, ensuring compliance with enterprise governance, policies, standards, and best practices.
- Establish and support enterprise data governance functions, architecture review boards, and governance forums, including developing Terms of Reference (ToRs).
- Provide architectural leadership and guidance for strategic data initiatives, enterprise data platforms, and data product development.
- Collaborate with business stakeholders, enterprise architects, solution architects, and engineering teams to define scalable and future-ready data solutions.
- Evaluate and recommend enterprise data architecture methodologies, technologies, and tools to support business transformation.
- Promote adoption of modern data architecture approaches, including Data Lake, Data Mesh, Data Fabric, Hybrid Architectures, and AI-enabled data ecosystems.
- Drive continuous improvement by identifying opportunities to enhance enterprise data architecture capabilities, governance, and operating models.
- Stay informed of emerging technologies, industry trends, and regulatory developments to ensure the organization's data architecture remains current and effective.
Requirements
What you’ll need- 9+ years’ experience
- Proven experience designing and delivering enterprise data architecture strategies, policies, standards, and target-state architectures.
- Demonstrated experience establishing enterprise data governance functions, developing governance frameworks, drafting Terms of Reference (ToRs), and leading architecture review forums.
- Strong experience designing enterprise-wide data flows, integration architectures, and transition-state roadmaps across multiple business domains.
- Experience reviewing and approving data architecture artefacts in accordance with enterprise policies, governance standards, and architectural principles.
- Strong knowledge of enterprise data modelling methodologies and industry-standard models such as FSLDM, BIRD, or equivalent frameworks.
- Solid understanding of modern data architecture paradigms, including Data Lake, Data Mesh, Data Fabric, Hybrid Architectures, and Agentic AI concepts.
- Excellent stakeholder management, communication, facilitation, and decision-making skills.
- Strong analytical and problem-solving abilities, with experience influencing architecture decisions in complex enterprise environments.
- Enterprise data modelling experience using industry-standard modelling tools.
- Experience evaluating, selecting, and implementing enterprise data architecture tools and technologies.
- Hands-on experience with cloud data platforms such as Databricks, Snowflake, or equivalent.
- Experience with enterprise data governance and metadata management platforms such as Collibra.
- Familiarity with Enterprise Architecture tools, including LeanIX, Ardoq, or similar platforms.
- Experience working in Financial Services, Banking, or other highly regulated industries.
Benefits
Comp & perks- Employees can work remotely