Lead Data Architect

Speria; Atlanta (GA); On-site; USD 150,000 - 210,000; Full time

Job summary

Speria in the United States (Atlanta area) seeks a Principal Platform Data Architect to lead the design, implementation, and evolution of enterprise-grade data systems. You will architect modern data platforms, semantic layers, telemetry pipelines, and agentic AI orchestration powering analytics, AI, and operational excellence.

You will ensure data flows across the business, enabling scalable, secure systems for global customers with collaboration across cross-functional teams.

Qualifications

• 10+ years experience in enterprise data architecture and engineering.
• Expertise with SQL Server, Databricks, Azure Data Lake, Synapse, Purview.
• Strong proficiency in Python, Spark, and semantic modeling tools.
• Hands-on experience with OWL, RDF, SPARQL.
• Deep understanding of data lineage, catalogs, knowledge graphs.

Responsibilities

• Architect unified data models for modular monoliths and microservices.
• Design data lakes, warehouses, and ETL pipelines with Databricks, SQL Server, Synapse, Delta Lake.
• Define data governance, metadata management, and observability standards.
• Develop ontology frameworks using OWL, RDF, SPARQL for semantic interoperability.
• Integrate structured and unstructured data into semantic layers for AI and analytics.
• Build and optimize high-volume ETL/ELT pipelines using Spark, Python, SQL.
• Implement data lineage, schema evolution, and data quality monitoring.
• Develop semantic telemetry pipelines for real-time analytics and AI agents.
• Manage cloud-native data infrastructure including Azure Data Factory, Event Hubs, Blob Storage.
• Prototype agentic AI workflows using orchestration frameworks.

Skills

Data architecture

SQL Server

Databricks

Azure Data Lake

Azure Synapse

Purview

Python

Spark

Semantic modeling

OWL/RDF/SPARQL

Tools

Azure Data Factory

Event Hubs

Blob Storage

Job description

Join Speria— Build Technology That Feeds the World

Wes tackling one of humanitys biggest challenges: feeding a growing population sustainably. Our AI-powered platform gives producers real-time insight to boost yield, improve animal welfare, and protect the planet.

Join us and build technology that truly impacts the world.

Why This Role Matters

As a Principal Platform Data Architect, you will lead the design, implementation, and evolution of enterprise-grade data systems. You will architect modern data platforms, semantic layers, telemetry pipelines, and agentic AI orchestration that power analytics, AI, and operational excellence. Your work directly shapes how data flows across the business and enables intelligent, scalable, and secure systems that support global customers.

What Youll Do

What Youll Do

• 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 data governance, metadata management, and observability standards.
• Develop ontology frameworks using OWL, RDF, SPARQL for semantic interoperability.
• Integrate structured and unstructured data into semantic layers for AI and analytics.
• Build and optimize high-volume ETL/ELT pipelines using Spark, Python, SQL.
• Implement data lineage, schema evolution, and data quality monitoring.
• Develop semantic telemetry pipelines for real-time analytics and AI agents.
• Manage cloud-native data infrastructure including Azure Data Factory, Event Hubs, Blob Storage.
• Prototype agentic AI workflows using orchestration frameworks.

What You Bring

What You Bring

• 10+ years experience in enterprise data architecture and engineering.
• Expertise with SQL Server, Databricks, Azure Data Lake, Synapse, Purview.
• Strong proficiency in Python, Spark, and semantic modeling tools.
• Hands-on experience with OWL, RDF, SPARQL.
• Deep understanding of data lineage, catalogs, knowledge graphs.

Youll Thrive If You Have Experience In:

Youll Thrive If You Have Experience In:

• Certifications in cloud architecture (Azure, AWS), data modeling, semantic technologies.
• Regulated industries (AgTech, FoodTech, Pharma, Healthcare).
• Controlled vocabularies, taxonomies, linked data.
• Agentic AI frameworks, vector databases, semantic telemetry.

Success Metrics

Success Metrics

• Reduction in support tickets and performance bottlenecks tied to data architecture.
• Seamless integration of semantic models across business domains.
• Acceleration of AI/analytics initiatives through strong data infrastructure.
• Adoption of ontology-driven architecture across teams.