Principal Data Architect

Speria; Atlanta (GA); On-site; USD 120,000 - 150,000; Full time

Job summary

Speria is seeking a Principal Data Architect who will lead the design and implementation of enterprise-grade data systems. You will architect modern data platforms supporting analytics and operational excellence.

The successful candidate will have over 10 years of experience, deep knowledge in data governance, SQL Server, and cloud technologies like Azure. This role is critical in enabling intelligent and scalable systems for global customers.

Qualifications

• 10+ years experience in enterprise data architecture and engineering.
• Expertise with SQL Server, Databricks, Azure Data Lake, Synapse, and Purview.
• Strong proficiency in Python, Spark, and semantic modeling tools.

Responsibilities

• Architect unified data models supporting modular and microservices-based platforms.
• Design and implement data lakes and ETL pipelines.
• Define data governance and metadata management standards.

Skills

Enterprise data architecture

Data governance

Python

SQL

Spark

Semantic modeling

Education

Bachelor’s degree

Tools

SQL Server

Databricks

Azure Data Lake

Azure Synapse

OWW

SPARQL

Job description

Join Speria— Build Technology That Feeds the World

We’re tackling one of humanity’s 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 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 You’ll Do (Job Summary)

• 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

• 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.
• Bachelor’s degree.

You’ll 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.
• High-growth SaaS environments.
• Agentic AI frameworks, vector databases, semantic telemetry.

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.