Data Architect

Position Summary

This role will play a key role in the architecture, delivery and governance of reporting and data delivery at Phibro. This hands on technical role requires proven experience and knowledge of data warehousing and IBM Cognos business intelligence, with emphasis on data architecture, sourcing, reporting and analytics through project lifecycles. Specific responsibilities include but are not limited to:

Key Responsibilities

1. Modern Data Architecture Leadership

• Own and enhance Phibro’s modernized data architecture built on Microsoft Fabric.
• Define technical standards for medallion architecture, CDC strategy, Fabric pipelines, optimization techniques, and Lakehouse/Warehouse usage.
• Evaluate and guide decisions on Spark vs. T-SQL warehouse design patterns.
• Oversee performance tuning to reduce compute consumption (CUs) across lakehouse notebooks, pipelines, and warehouse SQL objects.

2. Fabric Migration & Platform Modernization

• Lead the migration of legacy SQL Server/SSIS processes to Fabric Lakehouse, Warehouse, and Data Factory.
• Re-engineer existing pipelines, stored procedures, and ETL frameworks into scalable Fabric-native solutions.
• Manage mirroring, CDC enablement, and ingestion performance for JDE and other enterprise systems.
• Validate and refine Silver and Gold layer ingestion, including schema evolution, SCD Type 2, and materialized view refresh logic.

3. Data Engineering & Integration

• Design and maintain robust data ingestion pipelines for financials, sales, inventory, and master data domains.
• Partner with engineering teams to optimize Spark notebooks, Fabric pipelines, and delta lake tables.
• Ensure efficient CDC handling, bronze-to-gold transformations, and dependency orchestration.
• Establish operational runbooks and streamline orchestration sequencing.

4. Data Warehouse, MDM, & Governance

• Architect scalable enterprise data models for Finance, Supply Chain, Sales, Animal Health operations, and Planning.
• Support MDM modernization initiatives such as Customer Master redesign and Business Unit Master optimization.
• Promote data quality, auditability, lineage, and governance using Purview.
• Establish standards for schema design, keys, constraints, and gold-layer performance.

5. Business Partnership & Delivery

• Partner with Finance, Supply Chain, Commercial, and Production teams to understand reporting and analytics needs.
• Support month-end close processes through reliable data pipelines and validated warehouse layers.
• Provide guidance to leadership on capacity planning, cost optimization, and architecture selection.
• Collaborate with vendors (Microsoft, Virtusa, Qlik, etc.) on engineering, troubleshooting, and roadmap planning.

Required Skills and Experience

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related field.
• 15+ years of experience in data architecture, data engineering, and enterprise data platform delivery.
• Deep expertise with:
  • Microsoft SQL Server, SSIS,
  • Azure SQL Database, Azure SQL Managed Instance, Azure Data Factory (ADF)
  • ETL/ELT frameworks and enterprise data integration
  • Data warehousing and dimensional modeling
  • Data modeling and warehouse design
  • Change Data Capture (CDC)
  • Data governance and metadata management
• Proven experience modernizing legacy reporting and data platforms into cloud-based architectures.
• Experience supporting financial reporting, operational reporting, and month-end business processes.
• Strong understanding of enterprise integration patterns, cloud data architectures, and analytics platforms.

Preferred Qualifications

• Experience with Microsoft Fabric, including Lakehouse, Warehouse, Data Factory, Pipelines, Spark, and OneLake.
• Microsoft Azure Data Engineering or Fabric certification.
• Experience with Qlik Replicate, Databricks, Synapse Analytics, or comparable modern data platforms.
• Familiarity with Master Data Management (MDM) frameworks and data governance tools such as Microsoft Purview.
• Experience with Power BI, IBM Cognos, or similar enterprise analytics platforms.
• Experience integrating ERP systems such as JD Edwards (JDE), Oracle EBS, or similar enterprise applications.
• Experience supporting global manufacturing, supply chain, or life sciences organizations.

Key Technologies

• Microsoft Fabric: Lakehouse, Warehouse, Pipelines, CDC, Mirroring, Spark
• Azure: Data Factory, SQL Database, Managed Instance, Data Lake Storage
• SQL Server / SSIS
• Data Modeling: SCDs, star schema, dimensional modeling
• Visualization: Power BI, Cognos
• Governance: Purview
• ETL/ELT: Qlik Replicate, ADF, T-SQL, Spark