Associate Distinguished Engineer (Cloud Architecture, Cloud Infrastructure - AWS, Data Modeling, Master data management, Snowflake, ETL)

<p><strong>Requirements</strong></p><ul><li>15+ years of experience in Data Engineering, Data Architecture, or Enterprise Data Leadership roles.</li><li>Proven experience building and delivering enterprise-scale data platforms across large, complex, multi-business-unit organizations.</li><li>Strong expertise in Snowflake, including architecture, performance optimization, cost management, governance, and data sharing.</li><li>Strong hands-on experience in Data Modeling, including dimensional modeling and data vault methodologies.</li><li>Strong understanding of ETL concepts, data integration, data transformation, and data pipeline design.</li><li>Expert-level experience with Cloud Architecture and designing scalable, secure, and high-performing data ecosystems.</li><li>Expert-level hands-on experience with AWS Cloud Infrastructure and cloud-native data services.</li><li>Demonstrated experience delivering at least two enterprise Master Data Management (MDM) programs with direct accountability for match, merge, survivorship, and data stewardship decisions.</li><li>Experience implementing and governing enterprise data platforms using modern data management and governance frameworks.</li><li>Strong experience with semantic layers, business ontologies, and shared enterprise data models across multiple business domains.</li><li>Hands-on experience with enterprise MDM platforms such as Reltio, Informatica MDM, Stibo, Tamr, or similar.</li><li>Experience with data governance and cataloging solutions such as Collibra, including catalog, lineage, policy management, workflow, and user adoption.</li><li>Experience implementing data quality frameworks and controls using tools such as Soda, Great Expectations, or similar platforms.</li><li>Strong knowledge of cloud-based data ecosystems across AWS and Google Cloud environments.</li><li>Experience with dbt, orchestration frameworks, streaming architectures, batch processing, and modern data engineering practices.</li><li>Strong stakeholder management skills with the ability to engage executive leadership and influence strategic data decisions.</li><li>Proven experience defining and advocating foundational data initiatives while balancing business priorities and delivery timelines.</li><li>Strong consulting, client-facing, communication, and leadership capabilities.</li><li>Experience working in organizations with complex and diverse source systems resulting from acquisitions, mergers, or legacy technology landscapes.</li><li>Ability to translate complex data concepts into business outcomes for executive and non-technical stakeholders.</li></ul><p><strong>Responsibilities</strong></p><ul><li>Lead the design, architecture, and delivery of enterprise-scale data platforms that support strategic business objectives.</li><li>Act as a trusted advisor to senior client stakeholders and data leadership teams on data strategy, architecture, governance, and modernization initiatives.</li><li>Drive enterprise data architecture decisions and establish scalable frameworks, standards, and best practices.</li><li>Define and implement enterprise-wide Master Data Management strategies, including data quality, match and merge processes, survivorship rules, and governance models.</li><li>Design and establish semantic layers, business ontologies, and unified enterprise data models that enable consistent business definitions across functions.</li><li>Architect, optimize, and govern Snowflake-based data platforms to maximize scalability, performance, security, and cost efficiency.</li><li>Lead data modeling initiatives and ensure implementation of robust logical, conceptual, and physical data models.</li><li>Design and implement modern cloud data architectures leveraging AWS technologies and cloud-native services.</li><li>Oversee the development of scalable ETL and ELT frameworks, data pipelines, and integration solutions.</li><li>Establish enterprise data governance, metadata management, lineage, cataloging, and compliance processes.</li><li>Implement and enforce data quality controls, monitoring frameworks, and validation processes throughout the data lifecycle.</li><li>Collaborate closely with engineering and delivery teams to ensure architectural standards are effectively translated into implementation.</li><li>Evaluate and modernize legacy data platforms, warehouses, reporting ecosystems, and redundant data management solutions.</li><li>Facilitate alignment between business stakeholders to resolve complex data ownership, entity definition, and governance challenges.</li><li>Drive adoption of reusable data products, accelerators, and shared platform capabilities across the organization.</li><li>Enable data foundations that support analytics, AI, machine learning, and emerging intelligent applications.</li><li>Mentor architects, engineers, and data leaders while fostering a culture of data excellence and innovation.</li><li>Provide technical leadership throughout the entire project lifecycle, from strategy and architecture through implementation and operationalization.</li><li>Support proposal discussions, solution planning, technology evaluations, and strategic transformation initiatives.&#xa0;</li><li>Ensure enterprise data solutions are scalable, secure, governed, and aligned with long-term business goals.</li></ul>