Senior Data Architect

Senior Data Architect

The Senior Data Architect will be responsible for creating, publishing, and maintaining the enterprise data platform reference architecture to enable repeatable implementations across teams and operating companies.

Key Responsibilities

• Create and maintain the enterprise data platform reference architecture (principles, target-state, standards, patterns, and guardrails) to enable repeatable implementations across teams and operating companies.
• Lead architecture review forums, document decisions (trade-offs, rationale, and approved patterns), and manage exceptions to ensure consistent adoption and controlled evolution of the architecture.
• Convert business and technical needs into implementation-ready architecture designs, source-to-target mappings, and technical specifications; partner with BAs/PMs as needed while remaining accountable for the technical stack definition.
• Define enterprise lake/lakehouse/warehouse patterns (e.g., medallion/bronze-silver-gold), data product conventions, and semantic modeling approaches to support governed self-service BI and downstream AI consumption.
• Lead data modeling practices (e.g., dimensional, 3NF, Data Vault), define conformed entities and KPI/metric definitions, and establish semantic layer standards for consistent analytics.
• Design data architectures that support AI/ML lifecycles, including feature-ready datasets, training/validation data management, experiment reproducibility, and scalable data feeds for model inference.
• Define patterns for unstructured/semi-structured data (documents, images, logs) including extraction, enrichment, indexing, and governance for retrieval-augmented generation (RAG) and knowledge experiences.
• Partner with governance teams to define data domains, ownership, stewardship, glossary, lineage, and data quality controls; establish certification/curation processes for authoritative datasets.
• Define and enforce controls for data classification, access (RBAC/ABAC), encryption, retention, auditing, and privacy-by-design (including PII/PHI where applicable).
• Define integration patterns for APIs, events, CDC, and batch ingestion; ensure interoperability across source systems and downstream consumers.
• Drive reference architecture proof-of-concepts, codify learnings into standards, and create rollout/enablement assets (templates, checklists, runbooks) for scaled adoption.
• Establish monitoring and operational patterns (SLAs/SLOs, data observability, incident/runbook standards) and guide teams on performance and cost optimization.
• Communicate architecture decisions to technical and non-technical audiences; mentor engineers/architects and elevate architectural maturity across the organization.

Requirements

• 8+ years of experience in data engineering, analytics engineering, platform engineering, or data architecture, including ownership of enterprise data platform designs.
• Proven experience creating and maintaining reference architectures, standards, and reusable patterns (not just one-off solution architectures), including the ability to drive adoption through governance and enablement.
• Experience in industrial manufacturing preferred; awareness of 2 or more key domains from : procurement, supply chain, production planning, sales / customer service, and / or financial reporting will be a strong plus
• Experience with one or more ERPs as source systems, eg Oracle, SAP, Syteline, JD Edwards, Infor XA will be a strong plus
• Strong expertise with modern cloud data architectures (lakehouse/warehouse) and end-to-end pipeline design (batch and streaming).
• Deep proficiency in data modeling, including dimensional modeling and conformed data design; strong SQL skills and ability to review/guide transformation logic.
• Experience enabling AI/ML or advanced analytics use cases through data architecture (e.g., curated training/validation datasets, feature readiness, inference data flows, reproducible pipelines).
• Strong understanding of data governance practices (domains, ownership, lineage, glossary, metadata management) and data quality controls.
• Strong knowledge of security patterns for data platforms (identity-based access, least privilege, auditing, encryption, secrets management) and privacy-by-design.
• Ability to create clear architecture artifacts (reference docs, standards, templates, decision records) and lead architecture/design reviews with cross-functional stakeholders.
• Bachelor?s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

Work Arrangements

• Full-time position with a standard work schedule.
• Remote work is not specified, but may be available with approval from management.
• Quarterly office visits may be required for team meetings and collaboration.
• Travel requirements are not specified.