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

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.

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.