Senior Data Architect

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.

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/Db Versions 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.

Startdate: ASAP.

Compensation:
Negotiable.

• 15+ years in data/database engineering; 5–8+ years owning data/DB architecture for customer facing 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.

• 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).

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.