Data Architect

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

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