> Markdown version of [/jobs/ext/4571057-data-architect](https://www.wearedevelopers.com/jobs/ext/4571057-data-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Architect - **Company:** Alto-Shaam, Inc. - **Location:** Menomonee Falls, WI, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, ARM Architecture, Automation of Tests, BigQuery, Business Systems, Cloud Computing, Cloud Database, Information Systems, Continuous Integration, Data Architecture, Information Engineering, Data Security, Data Structures, Database Testing, Dimensional Modeling, Data Intelligence, Python (Programming Language), Operational Databases, Reference Data, Cloud Services, SAP FI, SQL Databases, Oracle Fusion Middleware, Data Streaming, Cloud Platform System, Bi Publisher, Snowflake, Information Technology, Integration Frameworks, Oracle Integration, Software Version Control, Databricks - **Published:** November 4, 2026 - **Apply:** https://jobs.smartrecruiters.com/Alto-Shaam/744000159500929-data-architect ## About the Role For a candidate to be successful as a Data Architect they must have: * Bachelor's degree in Computer Science, Information Systems, Engineering or a related discipline, or equivalent experience, with 5-8 years (6+ preferred) in data engineering, analytics engineering or similar. * Demonstrated experience owning the design of a production data warehouse model spanning 3 or more source systems. * Expert SQL and strong Python; hands-on dimensional modeling (Kimball or similar) in production. * Production experience on a cloud data platform (Snowflake or similar, such as Databricks, Fabric or BigQuery) and with ELT and transformation tools (Fivetran, dbt or similar). * Experience with version control, CI/CD and automated data testing. * Oracle Fusion Cloud data experience (BICC and BI Publisher extracts, Fusion data structures, ideally Fusion Data Intelligence) or deep experience with another large ERP, and ERP finance or supply chain data modeling, is strongly preferred. * Manufacturing or MES data familiarity; semantic-layer tools (Snowflake semantic views, Cortex or similar); cloud services (AWS or similar) and integration platforms (Oracle Integration Cloud or similar); streaming, IoT or equipment telemetry data; cloud data platform certification (SnowPro Core or similar); and experience building data for AI and LLM consumers are desirable. * Strong communication skills, with the ability to explain technical trade-offs to non-technical leaders. ## Description 1. Designs and builds the platform's data model, including dimensional models and conformed dimensions shared across finance, manufacturing, sales and service (customer, item, location, fiscal calendar). 2. Documents design decisions as architecture decision records so the platform's design is written down and repeatable. 3. Owns ingestion from Oracle Fusion Cloud, CRM, connected-equipment data and file-based feeds, including connector setup, monitoring and pipeline health. 4. Designs role-based access and data security, dev/test/production environments, CI/CD and orchestration, and warehouse cost management. 5. Puts data quality and governance in place early: data contracts and automated testing (for example, dbt tests), lineage, and master and reference data practices. 6. Builds and extends the semantic layer that dashboards and AI tools query directly. 7. Leads the migration of historical data from legacy business systems into the new platform, reconciling it with current ERP data and documenting legacy business rules and lineage. 8. Translates business requirements into data models and presents design trade-offs to technical and non-technical stakeholders. 9. Partners with the integration team on how data moves between systems (Oracle Integration Cloud or similar) and helps design the data and integration approach for new manufacturing systems, connected-equipment data and future applications. 10. Coaches colleagues who do part-time data work and sets the standards, documentation and onboarding materials for future team members.