Data Architect

Senior Data Architect

Location: Atlanta, GA - (Fully onsite for first 6 months then moves to hybrid 3 days per week in office)

Pay: $160k bonus

*No sponsorship is available at this time and no third parties*

About The Role

We are seeking a highly skilled and hands-on Senior Data Architect to lead the design, implementation, and ongoing evolution of enterprise-grade data systems. This role is ideal for a seasoned technologist who thrives in complex environments and is passionate about building scalable, secure, and intelligent data infrastructure that drives analytics, AI, and operational excellence.

In this deeply technical position, you’ll be responsible for architecting and deploying modern data platforms that enable semantic modeling, telemetry pipelines, and agentic AI orchestration. Success in this role requires advanced expertise in data engineering, cloud architecture, and semantic technologies.

Key Responsibilities

Architecture & Design

• Architect unified data models supporting modular monoliths and microservices-based platforms.
• Design and implement data lakes, data warehouses, and streaming/batch ETL pipelines using Databricks, SQL Server, Azure Synapse, and Delta Lake.
• Define and enforce data governance, metadata management, and observability standards across distributed systems.
• Develop ontology frameworks using technologies like OWL, RDF, and SPARQL to enable semantic interoperability and intelligent querying.
• Lead the integration of structured and unstructured data into semantic layers for use in vector databases, knowledge graphs, and agentic AI orchestration.
  
  

Hands-On Implementation

• Build and optimize ETL/ELT pipelines using Spark, Python, and SQL for high-volume, low-latency data processing.
• Implement data lineage tracking, schema evolution, and quality monitoring with tools such as Azure Purview, Great Expectations, or dbt.
• Develop and maintain semantic telemetry pipelines that power real-time analytics and AI agents.
• Configure and manage cloud-native data infrastructure, including Azure Data Factory, Event Hubs, and Blob Storage.
• Prototype and deploy agentic AI workflows leveraging orchestration frameworks and semantic data layers.
  
  

Collaboration & Leadership

• Partner with engineering, product, and AI teams to align data architecture with business goals and technical strategy.
• Mentor junior data engineers and support hiring, onboarding, and technical leadership initiatives.
• Evaluate and integrate emerging technologies such as data mesh, data fabric, and linked data ecosystems.
  
  

Qualifications

Required

• 10 years of experience in enterprise data architecture and engineering.
• Proven expertise with SQL Server, Databricks, Azure Data Lake, Synapse, and Purview.
• Strong proficiency in Python, Spark, and semantic modeling tools.
• Hands-on experience with OWL, RDF, SPARQL, or equivalent semantic technologies.
• Deep understanding of data lineage, data catalogs, and knowledge graph development.
• Demonstrated success in designing scalable data systems for analytics, AI, and operational workflows.
  
  

Preferred

• Certifications in cloud architecture (Azure, AWS), data modeling, or semantic technologies.
• Experience in regulated industries such as AgTech, FoodTech, Pharma, or Healthcare.
• Exposure to controlled vocabularies, taxonomies, and linked data ecosystems.
• Background in high-growth SaaS or transformation-stage enterprises.
• Familiarity with agentic AI frameworks, vector databases, and semantic telemetry.
  
  

Success Metrics

• Reduced support tickets and bottlenecks tied to data architecture.
• Seamless integration of semantic models across platforms and domains.
• Acceleration of AI and analytics initiatives through robust data infrastructure.
• Adoption of ontology-driven architecture across engineering and product teams.