Services
Sobryte Solutions provides senior-level, hands-on support to diagnose, stabilise and evolve business-critical data platforms across SQL Server and modern Azure-based environments.
Engagements are typically short, targeted, and outcome-driven — focused on resolving performance issues, reducing platform risk, and enabling teams to deliver with confidence.
Work is delivered directly within engineering teams, combining deep technical analysis with practical implementation support.
Consulting Services
Data Platform Stabilisation
- Hands-on investigation and remediation of performance, reliability and scalability issues across SQL Server and Azure-based data platforms.
- Typically engaged where platforms are under strain, poorly understood, or failing to meet operational demands.
SQL Server Performance Engineering
- Deep-dive analysis and optimisation of complex workloads, including query tuning, execution plan analysis and system-wide performance improvements.
- Focused on resolving bottlenecks in high-volume or business-critical environments.
Azure Databricks & Lakehouse Engineering
- Design and implementation of modern data platforms using Azure Databricks, including medallion architecture (Bronze, Silver, Gold), Delta Lake optimisation and secure data access via Unity Catalog.
- Work includes pipeline design, workload optimisation, and integration with Azure services such as Data Factory and Azure SQL.
- Engagements often involve migration or extension of existing SQL Server estates into scalable lakehouse architectures, with a strong focus on maintainability, governance and real-world operability.
Legacy Modernisation
- Controlled evolution of legacy SQL Server estates into scalable Azure-aligned data platforms, balancing risk, cost and delivery timelines.
- Emphasis is placed on pragmatic transition — not wholesale rewrites — ensuring continuity while improving long-term capability.
Regulatory Data Platforms
- Delivery and optimisation of regulatory reporting pipelines with a focus on accuracy, reconciliation and auditability.
- Experience includes building and validating data pipelines supporting regulated reporting requirements, where traceability and control are critical.
Engagement Model
Engagements are structured around clearly defined objectives, providing targeted advisory, technical assessment, or delivery support aligned to specific platform or performance challenges.
Typical engagement types:
- Rapid performance triage (1–3 days): diagnose bottlenecks and prioritise fixes
- Estate health check (1–2 weeks): risk assessment + stabilisation plan
- Modernisation planning (2–4 weeks): target architecture + roadmap
- Delivery support (ongoing): embedded support to accelerate execution
All engagements are designed to deliver clear, practical outcomes — not just recommendations.