Cynet systems Inc
Job Description
Pay Range: $55hr - $60hr
The Retail Data Modeler is responsible for designing, maintaining, and optimizing data models and pipelines for retail systems, including POS, inventory, CRM, and e-commerce platforms.
This role supports advanced analytics, data integration, and migration while ensuring high data quality and governance standards.
Responsibilities
Design and maintain conceptual, logical, and physical data models for retail systems.
Reverse engineer legacy system tables to understand relationships and dependencies.
Develop data migration mapping documents for one-time and ongoing data loads.
Write and optimize complex SQL queries for data profiling, transformation, validation, and reporting.
Build models supporting customer segmentation, product performance, and personalized marketing.
Collaborate with data engineers, business analysts, and merchandising teams to translate business requirements into scalable data solutions.
Develop and optimize ETL pipelines using tools like Talend, SSIS, or Azure Data Factory.
Architect and maintain retail data warehouses and data lakes for reporting and analytics.
Ensure data models comply with governance standards and maintain high data quality.
Maintain documentation of metadata, data lineage, definitions, and usage.
Monitor and tune data models for high-volume retail transactions and real-time analytics.
Identify opportunities to improve data reliability, efficiency, and overall quality.
Communicate technical concepts effectively to both technical and non-technical audiences.
Mandatory Skills
Data Modeling, Erwin, Snowflake, Python, Azure Synapse
Experience with cloud platforms such as Azure or GCP
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
7+ years of experience in data modeling, preferably in retail.
Expert-level SQL development and optimization skills.
Proficiency in Python and data modeling tools such as Erwin or ER/Studio.
Experience with retail cloud data solutions like Snowflake and Azure Synapse.
Strong understanding of OLTP and OLAP systems in a retail context.
Familiarity with retail KPIs including sell-through xx, inventory turnover, and customer lifetime value.
Preferred Skills
Experience with retail analytics platforms (e.g., SAS Retail, Oracle Retail, SAP CAR).
Knowledge of retail compliance standards (e.g., PCI DSS).
Certifications in cloud data services or retail analytics tools.
Exposure to AI/ML use cases in retail, including demand forecasting and recommendation engines.
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The Retail Data Modeler is responsible for designing, maintaining, and optimizing data models and pipelines for retail systems, including POS, inventory, CRM, and e-commerce platforms.
This role supports advanced analytics, data integration, and migration while ensuring high data quality and governance standards.
Responsibilities
Design and maintain conceptual, logical, and physical data models for retail systems.
Reverse engineer legacy system tables to understand relationships and dependencies.
Develop data migration mapping documents for one-time and ongoing data loads.
Write and optimize complex SQL queries for data profiling, transformation, validation, and reporting.
Build models supporting customer segmentation, product performance, and personalized marketing.
Collaborate with data engineers, business analysts, and merchandising teams to translate business requirements into scalable data solutions.
Develop and optimize ETL pipelines using tools like Talend, SSIS, or Azure Data Factory.
Architect and maintain retail data warehouses and data lakes for reporting and analytics.
Ensure data models comply with governance standards and maintain high data quality.
Maintain documentation of metadata, data lineage, definitions, and usage.
Monitor and tune data models for high-volume retail transactions and real-time analytics.
Identify opportunities to improve data reliability, efficiency, and overall quality.
Communicate technical concepts effectively to both technical and non-technical audiences.
Mandatory Skills
Data Modeling, Erwin, Snowflake, Python, Azure Synapse
Experience with cloud platforms such as Azure or GCP
Required Qualifications
Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
7+ years of experience in data modeling, preferably in retail.
Expert-level SQL development and optimization skills.
Proficiency in Python and data modeling tools such as Erwin or ER/Studio.
Experience with retail cloud data solutions like Snowflake and Azure Synapse.
Strong understanding of OLTP and OLAP systems in a retail context.
Familiarity with retail KPIs including sell-through xx, inventory turnover, and customer lifetime value.
Preferred Skills
Experience with retail analytics platforms (e.g., SAS Retail, Oracle Retail, SAP CAR).
Knowledge of retail compliance standards (e.g., PCI DSS).
Certifications in cloud data services or retail analytics tools.
Exposure to AI/ML use cases in retail, including demand forecasting and recommendation engines.
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