Data Architect

Key Responsibilities

• Architecture & Platform Design
• Translate business and technical requirements into scalable architectural blueprints and working solutions.
• Contribute to reference implementations and evaluations of design patterns for client and internal use.
• Pre-Sales & Technical Strategy
• Act as a technical SME during solution planning, helping shape client proposals and responding to RFPs/SOWs.
• Support internal solution reviews and provide input on architecture decisions for MicroAge initiatives.
• Participate in technical discovery to assess needs, define approach, and advise on platform readiness.
• Platform Implementation Support
• Delivery lead in the configuration and development of analytics platforms, including ingestion, transformation, and modeling layers.
• Support pipeline development using Azure Data Factory, Synapse Pipelines, Fabric Dataflows, and Databricks (PySpark).
• Guide implementation of dimensional, canonical, and Data Vault models to meet analytics use cases.
• Infrastructure & DevOps Enablement
• Provide expertise on CI/CD setup using Azure DevOps or GitHub Actions to automate deployment processes.
• Advises on environment management, versioning, and deployment strategy for Fabric-based solutions.
• Governance, Security & Compliance
• Support the design of secure architectures that incorporate RBAC, encryption, and data protection controls.
• Ensure internal and client solutions align with compliance standards such as HIPAA, GDPR, and contractual policies.
• Master Data Management & Quality
• Recommend MDM approaches including golden record design, data survivorship, and stewardship workflows.
• Design scalable data quality frameworks integrated with transformation pipelines and monitoring practices.
• DataOps & Agile Architecture
• Advocate for DataOps principles, including automated validation, environment consistency, and iterative enhancement.
• Contribute to repeatable architectures and modular design patterns that promote agility and reuse.
• Optimization & Performance Engineering
• Analyze and tune SQL and Spark-based workloads for performance and cost-efficiency.
• Recommend capacity-aware configurations, workload isolation techniques, and storage optimization patterns.
• Bi & Data Visualization Strategy
• Provide guidance on Power BI dataset modeling, DAX development, and data visualization best practices.
• Ensure analytical outputs are aligned to business needs and promote self-service capabilities.
• Internal SME Contribution
• Act as a Fabric and Azure data platform expert for MicroAge’s internal delivery efforts and platform evolution.
• Support internal project teams by providing architectural guidance and answering technical questions.
• Document reusable patterns, best practices, and platform reference materials to support knowledge sharing.

Required Qualifications

• 5+ years of experience in Azure data architecture, analytics engineering, or solution development.
• Expertise in Microsoft Fabric, Synapse, Data Factory, Databricks, and Power BI.
• Proficiency in SQL, Python, and PySpark for data modeling and transformation.
• Prominent ability to act as a technical SME in both client and internal settings.
• Strong communication and collaboration skills across cross-functional teams.
• Other relevant experience should include: Data Modeling and ETL Design, Big Data Technologies: Experience with Hadoop, Kafka, and Spark, Cloud Platforms: Familiarity with Azure, AWS, GCP, Snowflake, DynamoDB, Redshift, and Big Query, Database Technologies: Proficiency in both SQL and NoSQL databases, including PostgreSQL, MySQL, and MongoDB, Data Governance and Security: Understanding of best practices and compliance standards.