Solutions Architect-L3

Requirements

• Define and own end-to-end solution architecture for complex, data-intensive, multi-service systems on Microsoft Azure.
• Create and maintain architecture blueprints, HLDs, LLDs, data flow diagrams, and Architecture Decision Records (ADRs).
• Evaluate build-vs-buy decisions and drive technology selection with clear trade-off analysis across the Azure ecosystem.
• Ensure solutions satisfy non-functional requirements: performance, scalability, reliability, data freshness SLAs, and security.
• Architect end-to-end data pipelines using Azure Databricks spanning ingestion, transformation (Bronze / Silver / Gold layers), and serving.
• Design and govern data lakehouse solutions using Azure Data Lake Storage Gen2 (ADLS Gen2) and Delta Lake.
• Define data modelling standards (star schema, data vault, OBT) aligned to business reporting requirements in Power BI.
• Architect real-time and batch ingestion patterns using Azure Event Hubs, Azure Data Factory (ADF), and Databricks Structured Streaming.
• Drive adoption of Databricks Unity Catalog for data governance, lineage tracking, and fine-grained access control.
• Design cost-efficient Databricks cluster strategies (job clusters, instance pools, spot instances) and monitor DBU consumption.
• Establish data quality frameworks using Great Expectations, Databricks Lakehouse Monitoring, or equivalent tooling.
• Design scalable semantic layer and data models powering Power BI enterprise reports and dashboards.
• Define DirectQuery vs Import vs Composite model strategies for optimal Power BI performance and data freshness.
• Architect Power BI Premium / Fabric workspace strategies, including capacity planning and deployment pipelines (Dev / Test / Prod).
• Guide teams on DAX optimisation, row-level security (RLS), and Power BI paginated reports for operational reporting.
• Integrate Power BI with Azure Databricks via Partner Connect or Lakehouse connector for live analytics on Delta tables.
• Architect cloud-native solutions leveraging Azure services: Azure Synapse Analytics, Azure Purview, Azure Key Vault, Azure Monitor, and APIM.
• Define Infrastructure-as-Code (IaC) standards using Terraform or Bicep for repeatable, auditable deployments.
• Design Azure networking topology: VNets, Private Endpoints, NSGs, and hub-spoke patterns to secure data flows.
• Guide teams on containerisation (Docker, Azure Kubernetes Service) and Databricks-native MLflow for ML model management.
• Define disaster recovery, backup, and high-availability strategies across the Azure data platform stack.
• Serve as the primary technical point of contact across data engineering, analytics, product, and business teams.
• Provide technical mentorship to senior data engineers, analytics engineers, and tech leads.
• Lead architecture reviews, proof-of-concepts, and data platform migration spikes.
• Drive engineering best practices: modular pipeline design, idempotency, schema evolution, and CI/CD for data workflows.
• Partner with data owners, business analysts, and C-suite stakeholders to translate analytical requirements into robust data products.
• Present platform architecture, roadmaps, and data strategy to executive leadership with clarity and confidence.
• Establish data governance frameworks covering cataloguing (Azure Purview), data classification, and lineage.
• Ensure compliance with data privacy regulations (PDPB, GDPR) and security standards (ISO 27001, SOC 2) across the data platform.

Benefits

• 401(k)
• Health insurance
• Opportunity for advancement