Data Architect
About The Position
The Data Architect will define and own the enterprise data architecture across analytical, operational, and integration platforms. This role involves designing logical, physical, and conceptual data models to support various use cases including analytics, reporting, AI/ML, and operational needs. The architect will establish and enforce data architecture standards, patterns, and best practices, and design scalable cloud-based and hybrid data platforms such as data lakes, lakehouses, and warehouses. A key aspect of this role is partnering with business, analytics, security, and application teams to translate requirements into data solutions, ensuring alignment with security, governance, privacy, and compliance requirements. The Data Architect will also lead architecture reviews, provide technical guidance to data engineers and analytics teams, evaluate and recommend data technologies, and ensure data governance, metadata management, data quality, and lineage initiatives are upheld. Additionally, the role includes designing and building robust data pipelines (batch and streaming) for ingestion, transformation, and delivery, developing and optimizing ETL/ELT processes, and collaborating with engineers to implement architectural patterns in production systems. Ensuring pipelines are reliable, scalable, performant, and cost-efficient, troubleshooting data issues, and optimizing queries, storage, and processing are also key responsibilities. Support for CI/CD practices, automated testing, and monitoring for data workflows is expected.
Requirements
- Bachelor's degree in computer science, Information Systems, Engineering, or equivalent experience
- 8+ years of experience in data architecture and/or data engineering roles
- Proven experience designing enterprise-scale Azure
- Strong hands-on experience with Azure Data Lake Storage Gen2
- Strong hands-on experience with Azure Synapse Analytics
- Strong hands-on experience with Azure Data Factory
- Strong hands-on experience with Azure Databricks or Microsoft Fabric
- Advanced SQL skills
- Experience with Python
- 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
Nice To Haves
- Experience designing data architectures that support AI and machine learning workloads, including feature engineering, training, inference, and monitoring at scale.
- 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
Responsibilities
- 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
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
