Sr. Data Architect
Listed on 2026-09-09
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IT/Tech
Data Engineering
About The Role
The Senior Data Architect plays a foundational role in building the data infrastructure that will power Precor’s transition from spreadsheet-driven reporting to a governed, scalable analytics platform. This role is responsible for designing and governing the end-to-end data architecture across Microsoft Fabric, SAP ECC 6.0, and Google Big Query—ensuring data flows reliably from source systems to decision-makers across finance, operations, supply chain, and sales.
Working closely with the Manager of Data & Insights and cross‑functional business leaders, the Senior Data Architect sets technical standards, mentors the data team, and ensures the platform is structured to support machine learning, generative AI, and self‑service analytics both today and as the business grows.
- Design and govern scalable, fault-tolerant data pipelines spanning Microsoft Fabric, SAP ECC 6.0, and Google Big Query, ensuring reliable data flow from source systems through transformation to BI consumption.
- Architect end-to-end extraction from complex SAP ECC modules (FI/CO, MM, SD, PP), including medallion (bronze/silver/gold) layering within Fabric’s Lakehouse and One Lake environment.
- Establish patterns for batch and near-real-time ingestion, including change-data-capture (CDC) strategies that move SAP transactional data without overloading source systems.
- Design integration strategies that bridge Microsoft Azure and Google Cloud, enabling the two platforms to function as one coherent ecosystem.
- Evaluate and select ingestion, orchestration, and storage patterns that balance performance, cost, and long-term maintainability.
- Design enterprise semantic models structured for natural-language querying, Copilot integration, and downstream machine learning pipelines.
- Build and govern the business-logic layer that ensures AI-generated insights are grounded in validated, well-defined metrics.
- Standardize KPI and business definitions across the organization so that revenue, margin, and active units mean the same thing in every report and every AI-driven answer.
- Partner with data science to ensure feature stores and training datasets draw from architecturally sound, lineage-tracked sources.
- Anticipate emerging AI use cases—forecasting, anomaly detection, natural-language analytics—and ensure the architecture can support them without costly redesign.
- Establish data governance, lineage, security, and quality frameworks so that data can be trusted, audited, and traced to its source.
- Define role-based access and data-protection standards that keep sensitive financial, customer, and operational data secure across cloud platforms.
- Implement data quality monitoring and validation to catch and resolve issues before they surface in reports.
- Establish cost‑optimization and performance standards across Fabric capacity units, treating cloud spend as a managed business resource.
- Serve as the technical authority who translates business strategy into a clear data architecture roadmap and communicates trade‑offs in language executives can act on.
- Partner directly with leaders in finance, operations, supply chain, and sales to ensure the data platform is built around real business questions.
- Mentor and elevate data engineers, BI developers, and analysts, raising architectural maturity and delivery speed across the team.
- Set technical standards, review designs, and serve as the final escalation point for complex architectural decisions.
- Build and defend business cases for new investments in data tooling and capacity with clear, outcome‑focused reasoning.
- 5+ years in data engineering or architecture, with 1+ years in a senior or lead architect capacity.
- Deep, hands‑on expertise with Microsoft Fabric (One Lake, Lakehouse, Data Factory, Power BI semantic models and dataflows) or equivalent.
- Proven experience extracting and modeling data from SAP ECC 6.0, with real understanding of SAP’s underlying table structures and extraction challenges.
- Strong command of dimensional and semantic modeling (Kimball, star…
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