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Company Description đđŒWe'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 a scale â across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 36 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in! Job Description Requirements - 15+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Leadership roles. - Proven experience building and delivering enterprise-scale data platforms across large, complex, multi-business-unit organizations. - Strong expertise in Snowflake, including architecture, performance optimization, cost management, governance, and data sharing. - Strong hands-on experience in Data Modeling, including dimensional modeling and data vault methodologies. - Strong understanding of ETL concepts, data integration, data transformation, and data pipeline design. - Expert-level experience with Cloud Architecture and designing scalable, secure, and high-performing data ecosystems. - Expert-level hands-on experience with AWS Cloud Infrastructure and cloud-native data services. - Demonstrated experience delivering at least two enterprise Master Data Management (MDM) programs with direct accountability for match, merge, survivorship, and data stewardship decisions. - Experience implementing and governing enterprise data platforms using modern data management and governance frameworks. - Strong experience with semantic layers, business ontologies, and shared enterprise data models across multiple business domains. - Hands-on experience with enterprise MDM platforms such as Reltio, Informatica MDM, Stibo, Tamr, or similar. - Experience with data governance and cataloging solutions such as Collibra, including catalog, lineage, policy management, workflow, and user adoption. - Experience implementing data quality frameworks and controls using tools such as Soda, Great Expectations, or similar platforms. - Strong knowledge of cloud-based data ecosystems across AWS and Google Cloud environments. - Experience with dbt, orchestration frameworks, streaming architectures, batch processing, and modern data engineering practices. - Strong stakeholder management skills with the ability to engage executive leadership and influence strategic data decisions. - Proven experience defining and advocating foundational data initiatives while balancing business priorities and delivery timelines. - Strong consulting, client-facing, communication, and leadership capabilities. - Experience working in organizations with complex and diverse source systems resulting from acquisitions, mergers, or legacy technology landscapes. - Ability to translate complex data concepts into business outcomes for executive and non-technical stakeholders. Responsibilities - Lead the design, architecture, and delivery of enterprise-scale data platforms that support strategic business objectives. - Act as a trusted advisor to senior client stakeholders and data leadership teams on data strategy, architecture, governance, and modernization initiatives. - Drive enterprise data architecture decisions and establish scalable frameworks, standards, and best practices. - Define and implement enterprise-wide Master Data Management strategies, including data quality, match and merge processes, survivorship rules, and governance models. - Design and establish semantic layers, business ontologies, and unified enterprise data models that enable consistent business definitions across functions. - Architect, optimize, and govern Snowflake-based data platforms to maximize scalability, performance, security, and cost efficiency. - Lead data modeling initiatives and ensure implementation of robust logical, conceptual, and physical data models. - Design and implement modern cloud data architectures leveraging AWS technologies and cloud-native services. - Oversee the development of scalable ETL and ELT frameworks, data pipelines, and integration solutions. - Establish enterprise data governance, metadata management, lineage, cataloging, and compliance processes. - Implement and enforce data quality controls, monitoring frameworks, and validation processes throughout the data lifecycle. - Collaborate closely with engineering and delivery teams to ensure architectural standards are effectively translated into implementation. - Evaluate and modernize legacy data platforms, warehouses, reporting ecosystems, and redundant data management solutions. - Facilitate alignment between business stakeholders to resolve complex data ownership, entity definition, and governance challenges. - Drive adoption of reusable data products, accelerators, and shared platform capabilities across the organization. - Enable data foundations that support analytics, AI, machine learning, and emerging intelligent applications. - Mentor architects, engineers, and data leaders while fostering a culture of data excellence and innovation. - Provide technical leadership throughout the entire project lifecycle, from strategy and architecture through implementation and operationalization. - Support proposal discussions, solution planning, technology evaluations, and strategic transformation initiatives. - Ensure enterprise data solutions are scalable, secure, governed, and aligned with long-term business goals. Qualifications Bachelorâs or masterâs degree in computer science, Information Technology, or a related field.