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.
