Sr. Data Architect

At MTech Systems, our company mission is to increase yield in protein production to help feed the growing world population without compromising animal welfare or damaging the planet. We aim to create software that delivers real-time data to the entire supply chain that allows producers to get better insight into what is happening on their farms and what they can do to responsibly improve production.

MTech Systems is a prominent provider of tools for managing performance in Live Animal Protein Production. For over 30 years, MTech Systems has provided cutting-edge enterprise data solutions for all aspects of the live poultry operations cycle. We provide our customers with solutions in Business Intelligence, Live Production Accounting, Production Planning, and Remote Data Management—all through an integrated system. Our applications can currently be found running businesses on six continents in over 50 countries. MTech has built an international reputation for equipping our customers with the power to utilize comprehensive data to maximize profitability.

With over 250 employees globally, MTech Systems currently has main offices in Mexico, United States, and Brazil, with additional resources in key markets around the world. MTech Systems USA’s headquarters is based in Atlanta, Georgia and has approximately 90 team members in a casual, collaborative environment. Our work culture here is based on a commitment to helping our clients feed the world, resulting in a flexible and rewarding atmosphere. We are committed to maintaining a work culture that enhances collaboration, provides robust development tools, offers training programs, and allows for direct access to senior and executive management.

Job Summary

We’re looking for 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.

Responsibilities and Duties

Architecture & Design

• Architect unified data models that support 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 data quality monitoring using tools like Azure Purview, Great Expectations, or dbt.
• Develop and maintain semantic telemetry pipelines that feed 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 using 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 contribute to hiring, onboarding, and technical leadership initiatives.
• Evaluate and integrate emerging technologies including data mesh, data fabric, and linked data ecosystems.

Education and Required Qualifications

• 10+ years of experience in enterprise data architecture and engineering.
• Proven expertise in 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 technologies.
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