SCM Data Modeler

Work Mode: Hybrid 3 Days Onsite (Monday Tuesday Thursday)

Advanced experience with:

Python

PySpark

SQL

Data Modeling Techniques

ETL/ELT Development

Position Summary

SCM Data Innovation & Analytics is seeking an experienced SCM Data Modeler with strong Databricks expertise to design build and operationalize scalable Supply Chain data products that deliver measurable business value.

This role combines data modeling advanced analytics data engineering and product delivery to transform complex Supply Chain data into trusted governed and actionable insights.

The ideal candidate will have experience working with Supply Chain Procurement Supplier Management and Spend Analytics data leveraging modern cloud data platforms to support analytics reporting and AI-driven business solutions.

This role requires strong technical expertise in Databricks Python PySpark SQL and enterprise ERP data ecosystems.

Data Modeling & Analytics Solutions

Develop analytics solutions that address complex Supply Chain business challenges and opportunities.

Apply knowledge of procurement supplier performance spend analytics inventory and operational processes to deliver business-focused data products.

Translate business requirements into scalable data models that support reporting analytics and operational decision-making.

Data Engineering & Pipeline Development

Design build test and optimize scalable ETL/ELT pipelines using:

Databricks

Python

PySpark

SQL

Databricks Notebooks

Workflow and Pipeline Orchestration Frameworks

Develop and maintain reliable Silver and Gold layer data products following enterprise data architecture standards.

Ensure data quality reliability performance and scalability of analytical solutions.

Data Integration & Transformation

Transform and model data from multiple enterprise platforms including:

Oracle Cloud

SAP

Azure Data Warehouse (ADW)

Microsoft Dataflow

Dataverse

Other approved enterprise data sources

Build and maintain logical and physical data models that support Supply Chain analytics initiatives.

Analyze structured and unstructured Supply Chain data to generate actionable business insights.

Advanced Analytics AI & Machine Learning Develop and evaluate advanced analytics and AI-driven solutions where appropriate and support use cases involving:

Forecasting

Classification Models

Anomaly Detection

Text Analytics

Natural Language Processing (NLP)

Predictive Analytics

Databricks Platform Enablement

Utilize Databricks capabilities to accelerate data product development while ensuring governance and compliance standards are maintained including:

Databricks Notebooks

Jobs & Workflows

Unity Catalog

SQL Warehouses

Genie Code

Lakeflow / Lakeflow Designer

Documentation & Stakeholder Communication Create and maintain project documentation including:

Business Requirements

Solution Designs

Data Models

Idea Assessments

Technical Specifications

Status Reports

Communicate technical concepts solution designs and project updates effectively to both technical and non-technical stakeholders.

Partner with Supply Chain Analytics IT and business teams to ensure successful delivery and adoption of data products.

Required Qualifications

68 years of experience in Data Modeling Data Engineering Analytics or related disciplines.

Strong hands-on experience with Databricks.

Experience designing and implementing scalable enterprise data solutions

Strong understanding of data warehousing concepts dimensional modeling and data governance practices.

Experience integrating data from ERP and enterprise platforms.

Excellent problem-solving analytical and communication skills.

Ability to translate business requirements into scalable technical solutions.

Preferred Qualifications

Experience with Oracle Supply Chain Planning Cloud (SCM Cloud).

Experience working in Supply Chain Procurement Supplier Management or Spend Analytics domains.

Knowledge of Oil & Gas business operations and supply chain processes.

Experience with Machine Learning AI and advanced analytics solutions.

Familiarity with Microsoft Azure data ecosystem and modern cloud-based data architectures.

Experience working within Agile delivery environments.