Sr Data Architect 

Reports To: Director of Engineering

Department: Engineering

Location: Hybrid - Atlanta, GA

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

MTech builds customer-facing SaaS & analytics products used by global enterprise customers. You will own the database/data platform architecture that powers these products—driving performance, reliability, auditability, and cost efficiency at multi-tenant, multi-terabyte scale. Success is measured in hard outcomes: fewer P1s/support tickets, faster queries, bullet-proof ERP/SAP integrations, SLO compliance tied to SLAs, and audit ready evidence. 

Responsibilities and Duties  

Architecture & Design

• Own the end-to-end data architecture for enterprise SaaS (OLTP + analytical serving), including Azure SQL/MI, Databricks/Delta Lake, ADLS, Synapse/Fabric, and collaboration on Power BI semantic models (RLS, performance).
• Define and implement Information Lifecycle Management (ILM): hot/warm/cold tiers, 2-year OLTP retention, archive/nearline, and a BI mirror that enables rich analytics without impacting production workloads.
• Engineer ERP/SAP financial interfaces for idempotency, reconciliation, and traceability; design rollback/de-dup strategies and financial journal integrity controls.
• Govern schema evolution/DbVersions to prevent cross-customer regressions while achieving performance gains.
• Establish data SLOs (freshness, latency, correctness) mapped to customer SLAs; instrument monitoring/alerting and drive continuous improvement.

Operations & Observability

• Build observability for pipelines and interfaces (logs/metrics/traces, lineage, data quality gates) and correlate application telemetry (e.g., Stackify/Retrace) with DB performance for rapid rootcause analysis.
• Create incident playbooks (reprocess, reconcile, rollback) and drive MTTR down across data incidents.

Collaboration & Leadership

• Lead the DBA/DB engineering function (standards, reviews, capacity planning, HA/DR, on-call, performance/availability SLOs) and mentor data engineers.
• Partner with Product/Projects/BI to shape domain models that meet demanding customer reporting (e.g., Tyson Matrix) and planning needs without compromising OLTP.

Required Qualifications

• 15+ years in data/database engineering; 5–8+ years owning data/DB architecture for customerfacing SaaS/analytics at enterprise scale.
• Proven results at multi-terabyte scale (≥5 TB) with measurable improvements (P1 reduction, MTTR, query latency, cost/performance).
• Expertise in Azure SQL/MI, Databricks/Delta Lake, ADLS, Synapse/Fabric; deep SQL, partitioning/indexing, query plans, CDC, caching, schema versioning.
• Audit & SLA readiness: implemented controls/evidence to satisfy SOC 1 Type 2 (or equivalent) and run environments to SLOs linked to SLAs.
• ERP/SAP data interface craftsmanship: idempotent, reconciled, observable financial integrations.
• ILM/Archival + BI mirror design for queryable archives/analytics without OLTP impact.

Preferred Skills

• Power BI performance modeling (RLS, composite models, incremental refresh, DAX optimization).
• Modular monolith/microservices experience (plus, not required).
• Semantic tech (ontology/knowledge graphs), vector stores, and agentic AI orchestration experience (advantage, not required).

EEO Statement 

Integrated into our shared values is MTech’s commitment to diversity and equal employment opportunity. All qualified applicants will receive consideration for employment without regard to sex, age, race, color, creed, religion, national origin, disability, sexual orientation, gender identity, veteran status, military service, genetic information, or any other characteristic or conduct protected by law. MTech aims to maintain a global inclusive workplace where every person is regarded fairly, appreciated for their uniqueness, advanced according to their accomplishments, and encouraged to fulfill their highest potential. We believe in understanding and respecting differences among all people. Every individual at

MTech has an ongoing responsibility to respect and support a globally diverse environment.