

Transcend Softech LLC
Marketing Technology Data Modeler
β - Featured Role | Apply direct with Data Freelance Hub
This role is a Senior Marketing Technology Data Modeler for a long-term contract in Atlanta, GA, offering competitive pay. Requires 6+ years in data modeling, expertise in SQL and MarTech platforms, and a degree in a related field.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
June 30, 2026
π - Duration
Unknown
-
ποΈ - Location
On-site
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Atlanta, GA
-
π§ - Skills detailed
#Snowflake #Predictive Modeling #dbt (data build tool) #Computer Science #Data Management #Data Modeling #Datasets #Kafka (Apache Kafka) #Data Engineering #GDPR (General Data Protection Regulation) #AWS (Amazon Web Services) #Database Design #Data Science #Physical Data Model #BI (Business Intelligence) #Data Processing #Automation #GCP (Google Cloud Platform) #Data Vault #Cloud #Data Lineage #Azure #Documentation #Customer Segmentation #Redshift #Airflow #SQL (Structured Query Language) #Agile #Data Integration #Databricks #Data Architecture #Data Governance #Vault #Metadata #CRM (Customer Relationship Management) #Talend #Compliance #Matillion #"ETL (Extract #Transform #Load)" #Scala
Role description
Position: Marketing Technology Data Modeler
Location: Atlanta, GA
Long Term Contract
Experience Level: Senior
We are unable to provide sponsorship for this role.
Role Summary
The Marketing Technology Data Modeler is responsible for designing, implementing, and optimizing data models that power marketing analytics, customer insights, and personalized engagement strategies. This role bridges marketing, data engineering, and analytics teams to ensure scalable, high-quality data structures across MarTech platforms such as CDPs, CRM systems, and marketing automation tools.
Key Responsibilities
Data Modeling & Architecture
β’ Design conceptual, logical, and physical data models for marketing platforms and customer data systems (e.g., CDP, CRM, campaign tools)
β’ Build and maintain data schemas supporting customer 360, segmentation, attribution, and personalization
β’ Develop scalable models for structured and semi-structured data (behavioral, transactional, demographic)
MarTech Integration
β’ Collaborate with engineering teams to integrate data across systems such as Snowflake (Enterprise Data Platform), Adobe Experience Cloud, Integrating Channels etc.
β’ Define data flows and mapping between source systems, CDPs, and downstream Marketing activation and enablement apps
β’ Ensure interoperability between marketing platforms and enterprise data ecosystems
Data Governance & Quality
β’ Establish data standards, naming conventions, and metadata management practices
β’ Ensure data consistency, accuracy, and compliance (GDPR, CCPA where applicable)
β’ Partner with data governance teams to maintain data lineage and documentation
Analytics Enablement
β’ Enable advanced analytics use cases such as customer segmentation, campaign performance, attribution modeling, and predictive modeling
β’ Support BI/reporting teams with optimized datasets and semantic layers
β’ Collaborate with data scientists on feature engineering and model readiness
Stakeholder Collaboration
β’ Work closely with marketing, product, analytics, and engineering stakeholders to translate business requirements into data models
β’ Communicate technical concepts clearly to non-technical stakeholders
β’ Support agile delivery and continuous improvement efforts
Required Qualifications
β’ Bachelorβs or Masterβs degree in Computer Science, Data Engineering, Information Systems, or related field
β’ 6+ years of experience in data modeling, data architecture, or analytics engineering
β’ Strong expertise in:
β’ Data modeling techniques (dimensional modeling, star/snowflake schemas, Data Vault)
β’ SQL and database technologies (e.g., Snowflake, Redshift, Databricks, BigQuerry)
β’ Hands-on experience with MarTech platforms (Adobe, Salesforce, Segment, etc.)
β’ Experience working with large-scale datasets and cloud-based data platforms
β’ Understanding of marketing data concepts (customer journeys, attribution, segmentation)
Preferred Qualifications
β’ Experience with Customer Data Platforms (CDPs)
β’ Knowledge of real-time data processing (Kafka, streaming pipelines)
β’ Familiarity with data transformation tools (Talend, Matillion, Snow SQL, dbt, Airflow)
β’ Exposure to privacy and consent management frameworks
β’ Experience with APIs and data integration patterns
β’ Certification in cloud platforms (AWS, Azure, or GCP)
Key Skills
β’ Data modeling & database design
β’ Marketing analytics understanding
β’ Data integration and ETL/ELT
β’ Problem-solving and critical thinking
β’ Communication and stakeholder management
Position: Marketing Technology Data Modeler
Location: Atlanta, GA
Long Term Contract
Experience Level: Senior
We are unable to provide sponsorship for this role.
Role Summary
The Marketing Technology Data Modeler is responsible for designing, implementing, and optimizing data models that power marketing analytics, customer insights, and personalized engagement strategies. This role bridges marketing, data engineering, and analytics teams to ensure scalable, high-quality data structures across MarTech platforms such as CDPs, CRM systems, and marketing automation tools.
Key Responsibilities
Data Modeling & Architecture
β’ Design conceptual, logical, and physical data models for marketing platforms and customer data systems (e.g., CDP, CRM, campaign tools)
β’ Build and maintain data schemas supporting customer 360, segmentation, attribution, and personalization
β’ Develop scalable models for structured and semi-structured data (behavioral, transactional, demographic)
MarTech Integration
β’ Collaborate with engineering teams to integrate data across systems such as Snowflake (Enterprise Data Platform), Adobe Experience Cloud, Integrating Channels etc.
β’ Define data flows and mapping between source systems, CDPs, and downstream Marketing activation and enablement apps
β’ Ensure interoperability between marketing platforms and enterprise data ecosystems
Data Governance & Quality
β’ Establish data standards, naming conventions, and metadata management practices
β’ Ensure data consistency, accuracy, and compliance (GDPR, CCPA where applicable)
β’ Partner with data governance teams to maintain data lineage and documentation
Analytics Enablement
β’ Enable advanced analytics use cases such as customer segmentation, campaign performance, attribution modeling, and predictive modeling
β’ Support BI/reporting teams with optimized datasets and semantic layers
β’ Collaborate with data scientists on feature engineering and model readiness
Stakeholder Collaboration
β’ Work closely with marketing, product, analytics, and engineering stakeholders to translate business requirements into data models
β’ Communicate technical concepts clearly to non-technical stakeholders
β’ Support agile delivery and continuous improvement efforts
Required Qualifications
β’ Bachelorβs or Masterβs degree in Computer Science, Data Engineering, Information Systems, or related field
β’ 6+ years of experience in data modeling, data architecture, or analytics engineering
β’ Strong expertise in:
β’ Data modeling techniques (dimensional modeling, star/snowflake schemas, Data Vault)
β’ SQL and database technologies (e.g., Snowflake, Redshift, Databricks, BigQuerry)
β’ Hands-on experience with MarTech platforms (Adobe, Salesforce, Segment, etc.)
β’ Experience working with large-scale datasets and cloud-based data platforms
β’ Understanding of marketing data concepts (customer journeys, attribution, segmentation)
Preferred Qualifications
β’ Experience with Customer Data Platforms (CDPs)
β’ Knowledge of real-time data processing (Kafka, streaming pipelines)
β’ Familiarity with data transformation tools (Talend, Matillion, Snow SQL, dbt, Airflow)
β’ Exposure to privacy and consent management frameworks
β’ Experience with APIs and data integration patterns
β’ Certification in cloud platforms (AWS, Azure, or GCP)
Key Skills
β’ Data modeling & database design
β’ Marketing analytics understanding
β’ Data integration and ETL/ELT
β’ Problem-solving and critical thinking
β’ Communication and stakeholder management





