Agile Resources, Inc.
Overview
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
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. 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. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries
Food and Beverage Manufacturing
#J-18808-Ljbffr
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
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. 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. Seniority level
Mid-Senior level Employment type
Full-time Job function
Information Technology Industries
Food and Beverage Manufacturing
#J-18808-Ljbffr