What are the responsibilities and job description for the Data Architect position at Bravo Technical Resources?
Job Description
Enterprise Data Architecture & Cloud Strategy
Strategic Architecture & Enterprise Responsibilities
Post-Merger Data Integration & Platform Consolidation
Enterprise Lakehouse Architecture (Azure Microsoft Fabric)
Master Data Management (MDM) & Canonical Entity Design
Data Governance, Security & Compliance
Platform Ownership & Operational Leadership
(Repositioned after Strategic responsibilities for better narrative flow.)
BI Platform Administration
SQL & DB2 DBA Leadership
Production Deployments & DevOps
Observability, Monitoring & Orchestration
Cross-Functional Leadership
Technical Qualifications
Required
Preferred
Meet Your Recruiter
Logan Ridgley
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.
Strategic Architecture & Enterprise Responsibilities
Post-Merger Data Integration & Platform Consolidation
- 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.
Enterprise Lakehouse Architecture (Azure Microsoft Fabric)
- Design and operate Lakehouse architectures following Bronze/Silver/Gold patterns.
- Govern Fabric workspaces, Lakehouses, Pipelines, and semantic models.
- Define and maintain enterprise KPI frameworks and shared semantic layers.
- Ensure strong lineage, data quality, and operational observability.
Master Data Management (MDM) & Canonical Entity Design
- 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.
Data Governance, Security & Compliance
- 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.
Platform Ownership & Operational Leadership
(Repositioned after Strategic responsibilities for better narrative flow.)
BI Platform Administration
- 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.
SQL & DB2 DBA Leadership
- 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.
Production Deployments & DevOps
- 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.
Observability, Monitoring & Orchestration
- 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.
Cross-Functional Leadership
- 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, DevOps, and Lakehouse architecture.
Technical Qualifications
Required
- 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 Gen2.
- Strong SQL Server background with performance tuning expertise.
- Experience with DB2/iSeries data structures and migration.
- Familiarity with Cosmos DB/NoSQL and Databricks/PySpark.
Preferred
- Azure DevOps, CI/CD, and Infrastructure-as-Code (ARM/Bicep/Terraform).
- Azure Entra ID and least privilege security architecture.
- Azure cost governance and optimization.
- Strong experience with Microsoft Fabric.
Meet Your Recruiter
Logan Ridgley