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