SCM Data Modeler

Job Description

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

· 6–8 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.

Requirements
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 • 6–8 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.