Principal Data Architect
Speria
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.
• 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.
Vacancy posted 2 days ago
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