Data Architect

We are seeking an experienced Data Architect with strong expertise in information architecture and data modeling to serve as the data design authority within Osol's Data & Analytics practice. This role involves shaping how data is structured, governed, and trusted across client consulting engagements, industrial data platforms, and the Industrial AI initiatives deployed in our manufacturing plants. The primary focus is on consulting services, with an emphasis on modeling complex enterprise data end-to-end, preferably within finance and manufacturing domains. The ideal candidate is comfortable engaging with clients and senior executives, efficiently extracting critical information from busy subject-matter experts during concise, well-prepared sessions.

Key Responsibilities:
- Service Offerings: Define the scope, approach, deliverables, team structure, and estimates for Osol’s Data & Analytics services, including Data Strategy & Advisory, Data Engineering & Platform Modernization, Data Governance, Quality & Lineage, Business Intelligence & Analytics, and DataOps.
- Reusable Assets: Develop assessment frameworks, reference data architectures, industry-specific data model templates (starting with finance and manufacturing), and governance operating model templates.
- Presales: Lead discovery workshops, shape data solutions, author data architecture sections for proposals and RFP responses, estimate effort, and present to client executives alongside technology partners. Contribute to case studies and thought leadership initiatives.
- Delivery Leadership: Serve as lead data architect and design authority on engagements, guiding data engineers and BI developers while ensuring the quality of data designs and deliverables.
- AI-Assisted Development: Utilize AI coding tools such as Claude Code to generate and review code, SQL, and data models for complex use cases across multiple programming languages.
- Use-Case Data Readiness: Evaluate the availability, quality, history, and accessibility of plant data to prioritize Industrial AI use cases like predictive maintenance.
- Source Discovery: Collaborate with plant experts to document data sources including historians, control, maintenance, ERP, laboratory systems, and operator logbooks. Draft acquisition specifications that comply with read-only access and plant security protocols.
- Industrial Information Models: Design reusable, configuration-driven plant information model assets aligned with ISA-95 and ISO 14224 standards, including tag-to-asset mapping and AI-ready datasets to maximize reuse across plants and clients.
- Platform Data Design: Review industrial data platform scopes, requirements, and designs from a data perspective throughout their lifecycle. Advise architects on metadata, data quality, lineage, master and reference data, ownership, client data separation, and retention policies.
- RFI / RFP Evaluation: Assess vendor responses for enterprise data, analytics, and AI platforms from a data architecture viewpoint. Help define evaluation criteria and scoring, evaluate vendor demos and proofs of concept, and draft data requirements for RFP stages.

Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Software Engineering, Engineering, or a related discipline.
- At least 12 years of experience in data management, data warehousing, or data engineering, including a minimum of 5 years in data architecture or data modeling roles.
- Proven experience as lead data architect or modeler on at least two enterprise data platforms or data warehouse programs that have been productionized, ideally within consulting firms or technology vendors. Finance and/or manufacturing experience is strongly preferred.

Preferred Qualifications and Benefits:
- Certifications such as DAMA CDMP, TOGAF, or data platform certifications from Microsoft, Databricks, or Snowflake are advantageous.
- Deep expertise in enterprise data warehouse, data lake, and lakehouse platforms deployed in cloud, on-premises, or hybrid environments.
- Strong skills in conceptual, logical, and physical data modeling methodologies including dimensional (Kimball), normalized (3NF), and Data Vault 2.0.
- Comprehensive knowledge of information architecture components such as business glossaries, taxonomies, ontologies, canonical and semantic models, metadata, master and reference data, and data domain ownership.
- Familiarity with DAMA-DMBOK-aligned data governance practices covering data quality, lineage, classification, privacy, retention, and stewardship.
- Advanced SQL capabilities for profiling and analysis, along with working knowledge of ELT, change data capture, streaming, and batch processing patterns to effectively guide engineering teams.
- Domain expertise in finance (general ledger, chart of accounts, cost and profitability, management reporting) and manufacturing (plant historians, asset hierarchies, maintenance, and time-series data), including SAP or Oracle ERP structures.

This role offers the opportunity to lead impactful data architecture initiatives across cutting-edge industrial AI programs and enterprise data platforms, working closely with senior stakeholders and technology partners to drive data excellence.