Stabilising and Evolving Critical Data Platforms
Sobryte Solutions provides senior, hands-on support to diagnose, optimise and modernise business-critical data platforms across SQL Server, Azure and Databricks environments.
Engagements focus on resolving performance bottlenecks, reducing platform risk, and enabling teams to deliver reliably — particularly within finance, regulatory and operational reporting contexts.
Work is delivered directly within engineering teams, combining deep technical analysis with practical implementation to achieve measurable outcomes.
Core Areas of Support
- SQL Server performance optimisation, troubleshooting and workload remediation
- Design and delivery of Azure data platforms using Azure SQL, Data Factory and Databricks
- Implementation of Databricks lakehouse architectures (Bronze, Silver, Gold) with Delta Lake
- ETL development, transformation logic, and data warehouse design
- Stabilisation and refactoring of legacy database estates
- Design and delivery of regulatory and financial reporting data pipelines
Typical Engagements
Typically engaged by organisations with established teams that require senior technical depth to resolve complex issues, de-risk delivery, or accelerate progress in critical areas.
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Performance & Stability Deep-Dive
Root cause analysis of persistent SQL Server or data pipeline performance issues, with prioritised remediation actions. -
Architecture Review & Technical Assurance
Independent review of Azure or Databricks platform designs prior to implementation. -
Legacy Platform Risk Assessment
Assessment of ageing SQL Server estates, technical debt, and pragmatic modernisation options. -
Data Platform Modernisation
Migration or extension of existing platforms into Azure and Databricks-based architectures. -
Regulatory / Finance Data Pipeline Design
Support for complex derivations, controls, reconciliations, and auditability requirements. -
Short-Term Specialist Augmentation
Senior hands-on capability embedded within delivery teams during key phases.
Engagement Model
Engagements are typically short and focused, structured around clearly defined objectives and delivered collaboratively alongside internal teams.
The aim is to resolve immediate constraints while strengthening long-term platform resilience, clarity and ownership.
All work is execution-oriented — combining targeted diagnostic analysis with hands-on implementation support.