Data Architect

Enterprise Data Architecture & Cloud Strategy

• Architect modern enterprise data platforms across On‑Prem, Azure, and Fabric ecosystems.

• Define architectural standards, reusable patterns, roadmaps, and modernization strategies.

• Lead scalable ingestion, storage, transformation, and modeling frameworks.

• Drive cloud adoption with a focus on resiliency, standardization, and business alignment.

• Consolidate data environments, pipelines, and models across acquired companies.

• Integrate ERP, CRM, and operational systems into unified Lake/Lakehouse architectures.

• Establish reusable ingestion and onboarding frameworks for future acquisitions.

• Standardize canonical models and reduce duplicated or conflicting data assets.

• Design and operate Lakehouse architectures following Bronze/Silver/Gold patterns.

• Govern Fabric work spaces, Lake houses, Pipelines, and semantic models.

• Define and maintain enterprise KPI frameworks and shared semantic layers.

• Ensure strong lineage, data quality, and operational observability.

• Define canonical entities (Customer, Product, Vendor, Location, etc.).

• Implement pragmatic MDM-lite or hybrid models that scale without unnecessary overhead.

• Resolve identity conflicts, hierarchy mismatches, and attribute drift across systems.

• Establish metadata, stewardship roles, and entity lifecycle governance.

• Architect scalable governance models supporting acquisitions and enterprise growth.

• Implement domain isolation, RLS/CLS, data certification, and metadata standards.

• Ensure compliance with SOX, privacy, and corporate data security policies.

• Partner with security teams to enforce consistent controls across platforms.

• Oversee Power BI, Fabric, and on‑prem BI platforms.

• Govern workspace hierarchy, capacity usage, semantic models, and performance.

• Ensure reliability, scalability, and governed data access.

• Provide direction to SQL Server and DB2 DBAs for performance, HA/DR, and maintenance.

• Govern schema lifecycle, environment consistency, and change management.

• Support DB2 and legacy system modernization and migration strategies.

• Govern CI/CD and deployment pipelines across On‑Prem, Azure, and Fabric.

• Standardize automation, approvals, versioning, rollback, and SDLC practices.

• Manage deployments for ADF, Logic Apps, Azure SQL/Synapse, Cosmos DB, and Fabric.

• Architect end‑to‑end observability using New Relic.

• Implement dashboards, telemetry, alerting, and workload reliability standards.

• Govern enterprise scheduling and orchestration using Control‑M.

• Drive proactive monitoring across pipelines, databases, and Fabric workloads.

• Provide architectural leadership and direction across data engineering, BI, and DBA teams to ensure alignment with enterprise data strategy.

• Lead decision‑making on data platform patterns, governance standards, and modernization initiatives.

• Mentor technical teams and drive adoption of best practices in cloud data engineering, Dev Ops, and Lakehouse architecture.

• 12–15+ years in enterprise data architecture and cloud analytics.

• Expertise in data modeling, schema design, and large‑scale data systems.

• Advanced hands‑on experience with ADF, Azure SQL, Synapse, and ADLS Gen
  2.

• Strong SQL Server background with performance tuning expertise.

• Experience with DB2/iSeries data structures and migration.

• Familiarity with Cosmos DB/No
  
  SQL and Databricks/PySpark.

• Azure Dev Ops, CI/CD, and Infrastructure‑as‑Code (ARM/Bicep/Terraform).

• Azure Entra  least‑privilege security architecture.

• Azure cost governance and optimization.

• Strong experience with Microsoft Fabric.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.