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