1872 Consulting
This range is provided by 1872 Consulting. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
Base pay range $110,000.00/yr - $130,000.00/yr
Our client is a technology-driven organization focused on digital and data transformation across enterprise systems. They are building scalable, cloud-based data platforms to enable analytics, AI, and real-time insights across the business. The environment is remote-first, collaborative, and emphasizes hands-on technical excellence within modern Azure ecosystems.
Position Summary We’re seeking a Digital Data Architect to design and implement enterprise data architectures supporting analytics, AI/ML, and digital modernization. This individual contributor role focuses on data modeling, Azure-based architecture, and close collaboration with engineering teams. The ideal candidate combines strong data design skills with working knowledge of Azure cloud technologies and modern ELT/streaming practices.
Key Responsibilities
Design conceptual, logical, and physical data models for enterprise and domain-level systems.
Architect and optimize data platforms leveraging Azure Synapse, Databricks, Data Factory, Data Lake, and Cosmos DB.
Develop and oversee ETL/ELT frameworks for analytics and operational data systems.
Ensure data structures support AI/ML workloads and modern analytics use cases.
Collaborate with data engineers and architects to deliver scalable, governed solutions.
Apply best practices for data modeling, lineage, and performance optimization.
Maintain compliance with governance and security standards (GDPR, CCPA).
Key Performance Indicators
Quality and scalability of implemented data models.
Reduced latency and improved data pipeline efficiency.
Cross-team adoption and performance of designed architectures.
Required Qualifications
8–12 years in data architecture and modeling
Must have strong Data Architecture/Modeling experience in Azure environments
More experience with the following Azure data services the better: Azure Synapse, Databricks, Data Factory, Data Lake, Event Hubs, Cosmos DB.
Strong background in data modeling (conceptual, logical, and physical)
Advanced SQL proficiency
Nice to haves (in this order)
Building data pipelines with Python, Spark and/or Kafka is
Experience with ELT is a big nice to have
Familiarity with ML pipeline integration and Data Mesh/Data Fabric concepts.
Bachelor’s or Master’s Degree in Computer Science or a related field
Azure certifications (Data Engineer or Solutions Architect).
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Base pay range $110,000.00/yr - $130,000.00/yr
Our client is a technology-driven organization focused on digital and data transformation across enterprise systems. They are building scalable, cloud-based data platforms to enable analytics, AI, and real-time insights across the business. The environment is remote-first, collaborative, and emphasizes hands-on technical excellence within modern Azure ecosystems.
Position Summary We’re seeking a Digital Data Architect to design and implement enterprise data architectures supporting analytics, AI/ML, and digital modernization. This individual contributor role focuses on data modeling, Azure-based architecture, and close collaboration with engineering teams. The ideal candidate combines strong data design skills with working knowledge of Azure cloud technologies and modern ELT/streaming practices.
Key Responsibilities
Design conceptual, logical, and physical data models for enterprise and domain-level systems.
Architect and optimize data platforms leveraging Azure Synapse, Databricks, Data Factory, Data Lake, and Cosmos DB.
Develop and oversee ETL/ELT frameworks for analytics and operational data systems.
Ensure data structures support AI/ML workloads and modern analytics use cases.
Collaborate with data engineers and architects to deliver scalable, governed solutions.
Apply best practices for data modeling, lineage, and performance optimization.
Maintain compliance with governance and security standards (GDPR, CCPA).
Key Performance Indicators
Quality and scalability of implemented data models.
Reduced latency and improved data pipeline efficiency.
Cross-team adoption and performance of designed architectures.
Required Qualifications
8–12 years in data architecture and modeling
Must have strong Data Architecture/Modeling experience in Azure environments
More experience with the following Azure data services the better: Azure Synapse, Databricks, Data Factory, Data Lake, Event Hubs, Cosmos DB.
Strong background in data modeling (conceptual, logical, and physical)
Advanced SQL proficiency
Nice to haves (in this order)
Building data pipelines with Python, Spark and/or Kafka is
Experience with ELT is a big nice to have
Familiarity with ML pipeline integration and Data Mesh/Data Fabric concepts.
Bachelor’s or Master’s Degree in Computer Science or a related field
Azure certifications (Data Engineer or Solutions Architect).
#J-18808-Ljbffr