Data Architect

ESSENTIAL DUTIES AND RESPONSIBILITIES: 

Data Architecture (≈70%) 

• Define and own enterprise data architecture across analytical, operational, and integration platforms 
• Design logical, physical, and conceptual data models to support analytics, reporting, AI/ML, and operational use cases 
• Establish and enforce data architecture standards, patterns, and best practices 
• Design scalable cloud-based and hybrid data platforms (e.g., data lakes, lakehouses, warehouses) 
• Partner with business, analytics, security, and application teams to translate requirements into data solutions 
• Ensure data solutions align with security, governance, privacy, and compliance requirements 
• Lead architecture reviews and provide technical guidance to data engineers and analytics teams 
• Evaluate and recommend data technologies, tools, and platforms 
• Ensure data governance, metadata management, data quality, and lineage initiatives 

Data Engineering (≈30%) 

• Design and build robust data pipelines (batch and streaming) for ingestion, transformation, and delivery 
• Develop and optimize ETL/ELT processes using modern data engineering frameworks 
• Collaborate with engineers to implement architectural patterns in production systems 
• Ensure pipelines are reliable, scalable, performant, and cost-efficient 
• Troubleshoot data issues and optimize queries, storage, and processing 
• Support CI/CD practices, automated testing, and monitoring for data workflows 

EDUCATION, TRAINING, AND EXPERIENCE: 

• Bachelor's degree in computer science, Information Systems, Engineering, or equivalent experience 
• 8+ years of experience in data architecture and/or data engineering roles 

REQUIRED SKILLS: 

• Proven experience designing enterprise-scale Azure  
• Strong hands-on experience with:  
• Azure Data Lake Storage Gen2 
• Azure Synapse Analytics 
• Azure Data Factory 
• Azure Databricks or Microsoft Fabric 
• Advanced SQL skills and experience with Python (preferred) 
• Strong knowledge of data modeling, performance tuning, and cost optimization in Azure 
• Experience integrating data from SaaS, on-prem, and cloud-based systems 
• Ability to clearly communicate architectural decisions to both technical and non-technical stakeholders 
• Background with Data Governance Framework 

Preferred Skills: 

• Experience designing data architectures that support AI and machine learning workloads, including feature engineering, training, inference, and monitoring at scale. 

TOOLS, EQUIPMENT, AND SOFTWARE: 

• Experience with Microsoft Fabric (OneLake, Lakehouse, Warehouse, Power BI integration) 
• Familiarity with Power BI semantic models and analytics consumption patterns 
• Knowledge of Azure Purview / Microsoft Purview for data governance and lineage 
• Experience with event-driven and streaming architectures in Azure 
• Understanding of DataOps / DevOps practices in an Azure environment 
• Experience supporting regulated or security-conscious enterprise environments  

WORKING CONDITIONS AND PHYSICAL REQUIREMENTS:  

• Primarily indoor work in an office environment requiring long periods of sitting  
• Frequent utilization of manual dexterity and visualizing of a computer screen  
• No unusual physical requirements