Data Management Solution Architect

Data Management Solution ArchitectContract |Fully Remote|About the RoleGovernance frameworks only deliver value when they are wired into the underlying data and AI infrastructure, not bolted on after the fact. Our client places Data Governance Solution Architects inside client Data Governance programs to bridge the strategic and the technical. This role designs the end-to-end solution architecture that connects governance frameworks (decision rights, stewardship, policy) and the semantic layer (ontologies, glossary, metric definitions) to the data platforms, pipelines, and AI/ML workflows where data actually lives.The Solution Architect partners closely with the Data Governance Lead & Metadata Lead while also engaging deeply with client engineering teams. This is a hands-on architectural role and carries high visibility with both business stakeholders and technical leadership.Key ResponsibilitiesSolution Architecture; lead the design of the governance and metadata solution architecture connecting governance frameworks, catalog/metadata platforms, data platforms (warehouse, lake, lakehouse), and AI/ML systems.Semantic Layer Integration; design how governance and metadata systems serve and consume the semantic layer (ontologies, glossary terms, conformed metrics) so AI applications and analytics ground in the same business definitions.Metadata Integration Patterns; define and implement metadata flows: ingestion from source systems, lineage capture, and push to downstream consumers (BI, AI/ML, marketplaces, regulators).Tool-Agnostic Design; evaluate, recommend, and integrate platforms across catalog/governance (Collibra, Alation, Atlan, Purview, OpenMetadata), data (Snowflake, Databricks, BigQuery), and AI/ML tooling.Reference Architecture; develop reference patterns and reusable architectural artifacts that the client can replicate across domains and engagements.Build Oversight; provide oversight and review of build work executed by client engineering and consultants; ensure designs are implemented faithfully.Standards & Patterns; develop and maintain architectural standards covering metadata import/export, automation, lineage propagation, and AI data controls.Required Qualifications10+ years in data architecture, solution architecture, or enterprise architecture, with at least 4 years focused on data governance, metadata management, or data catalog solutions.Deep architectural experience across at least one major catalog/governance platform and at least one modern data platform (Snowflake, Databricks, BigQuery, or equivalent).Demonstrated experience designing solutions that integrate governance/metadata systems with AI/ML workflows: training data lineage, model metadata, feature store metadata, or equivalent.Strong understanding of metadata standards, APIs, and integration patterns (REST, event-driven, OpenLineage, OpenMetadata).Proven ability to lead architectural reviews, translate business strategy into technical designs, and influence senior technical and business stakeholders.Preferred QualificationsExperience designing AI Governance, Responsible AI, or AI Risk Management technical controls.Familiarity with semantic technologies and semantic layer platformsCDMP (Certified Data Management Professional) or DAMA-aligned credentials.Experience in regulated industries (life sciences, financial services, healthcare).What Success Looks LikeComplete a technical current-state assessment of governance, metadata, and AI/ML platforms; surface architectural constraints and integration gaps.Deliver a documented, approved solution architecture connecting governance, metadata, data platforms, and AI/ML systems; publish reference patterns and architectural standards.Operationalize metadata integration patterns across priority systems; embed AI data controls into the client's AI development and deployment lifecycle; oversee build work to ensure faithful implementation of the architecture.Align engineering, governance, and business leadership on the technical operating model.Produce reference architecture artifacts that the client and can replicate across domains.