Modern Data Platforms. Reliable Engineering. Scalable Analytics.
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§ Signs
We provide end-to-end database engineering, data engineering, cloud data platform, data migration, data warehousing and business intelligence services. Our engineers build, migrate, optimise and maintain modern data platforms on Snowflake, Databricks, Microsoft Fabric, Azure, SQL Server and Power BI, delivering secure, scalable, high-performance data solutions. We support organisations, consulting firms, system integrators, and technology partners seeking specialised database and data engineering expertise, through project-based engagements, consulting, implementation, migration, optimisation, production support and dedicated engineering resources.
Numbers differ between dashboards, and every meeting starts with a debate about the data.
Loads fail overnight, fixes are manual and nobody is alerted until users complain.
On-premises SQL Server or an old warehouse is slow, expensive and hard to change.
Snowflake credits, Databricks DBUs or Fabric capacity cost more each month without a clear reason.
Machine learning and AI projects stall because the underlying data is incomplete or ungoverned.
§ What we deliver
Choose an area to see the services in it.
dbtdbt
Microsoft Fabric
Power BI
Azure Data FactoryAzure Synapse AnalyticsAzure DevOps
SQL ServerMicrosoft FabricdbtPower BIMicrosoft FabricSQL Server§ Proof
Featured case study
This sports intelligence platform is designed to deliver real-time sports data, advanced analytics, and a community-driven prediction ecosystem.
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§ Approach
We review your sources, databases, pipelines and reports, and agree the priorities with your team.
You receive Cloud data platform assessment and roadmap
We choose the platform with you and design the target architecture: layers, security model, orchestration and cost guardrails.
You receive Target architecture and technical design document
A short proof of concept on your own data tests the riskiest assumption before a larger commitment.
You receive Proof of concept with findings and a recommendation
Pipelines, models and reports are built in iterations, with tests, CI/CD and reconciliation against the source systems.
You receive Tested pipelines, models and reports deployed through CI/CD
We monitor, support and tune the platform for performance and cost, or hand it over to your team with full documentation.
You receive Runbooks, monitoring dashboards and an optimisation backlog
We document the platform, train your team and agree the support model that suits you, from full handover to managed operations.
You receive Documentation, team walkthroughs and a support plan
§ Tech stack
Microsoft FabricAzure Data FactoryAzure Synapse AnalyticsSQL ServerdbtPower BIAzure DevOps§ Engagement models
A defined scope, timeline and deliverables, from design through go-live.
An agreed price for a clearly scoped implementation, such as a migration or a new warehouse.
Our engineers work under your contract, or as a subcontractor to consulting firms and system integrators.
Data engineers who join your team and work in your tools and processes.
Consultants and developers working remotely, with overlap in your working hours.
Architecture reviews, platform choices and design guidance for your own team.
Monitoring, incident handling and ongoing fixes for pipelines and databases in production.
A short, fixed-scope engagement to test an approach on your data or plan a migration.
§ FAQs
Snowflake, Databricks, Microsoft Fabric, Azure (Data Factory, Synapse Analytics, Data Lake Storage Gen2 and Azure SQL), Microsoft SQL Server, PostgreSQL, MySQL, MongoDB, dbt and Power BI. We are official Snowflake, Databricks and Microsoft partners.
Yes. We deliver on-premises to cloud database migration, legacy data warehouse modernisation, and migrations from SQL Server to Snowflake, Databricks and Microsoft Fabric, with data quality and reconciliation checks so the migrated data matches the source.
Project-based data engineering, fixed-price implementation projects, contract and subcontract engineering, dedicated data engineering resources, remote consulting and development, architecture and technical advisory, production support and maintenance, and short-term proofs of concept and migration assessments.
Yes. Our production support and managed data engineering services cover pipeline and job monitoring, incident management, database health checks, capacity planning, and ongoing performance and cost optimisation.
Yes. Besides end clients, we support consulting firms, system integrators and technology partners through contract and subcontract engineering, dedicated data engineering resources, and remote consulting and development.
Yes. Technical architecture reviews, proofs of concept and migration assessments are a common first step: they test the riskiest part of a plan on your own data before a larger commitment.
An assessment takes a few weeks. A first production pipeline or subject area usually follows soon after, and larger platforms or migrations are delivered in waves so value arrives early. We give a phased plan once we have seen your estate.
Defined work such as an assessment, a migration or a first warehouse can be fixed price. Ongoing roadmaps suit time and materials or dedicated engineers. We send a written estimate with its assumptions after a first call.
Least-privilege access, encryption, secrets in a vault, audit logging and data kept in your accounts and chosen regions. We work under NDA and design controls around your UK GDPR and Data Protection Act 2018 obligations.
Yes. Code lives in your repositories, the platform runs in your accounts, and there is no proprietary layer you need us to keep running.
§ In detail
We are partners of Snowflake, Databricks and Microsoft, so we recommend on your workloads. A short guide to where each one is strongest:
SQL-centreed warehousing, BI and secure data sharing, with very little platform administration.
Spark-heavy engineering, streaming and machine learning on open Delta tables.
Microsoft-centreed estates that want engineering, warehousing and Power BI under one capacity and one security model.
Data Factory, ADLS and Azure SQL for teams that want fine-grained control inside their own Azure landing zone.
Operational databases and smaller warehouses where a well-tuned relational database is the right answer.
The transformation and reporting layers we use on top of whichever platform you choose.
Everything is built in your cloud accounts and Git repositories, and documented for your team.
Architecture choices are written up as short decision records before we build.
We pair with your engineers so they can run and extend the platform after go-live.
Projects, fixed-price implementations, subcontracting for consultancies or dedicated engineers.
Fintech apps, payments, risk scoring and analytics for banks, lenders and startups.
Telehealth, patient engagement and clinical data platforms built with privacy in mind.
Sales, inventory and customer data unified for reporting, forecasting and personalisation.
Shop-floor apps, IoT data and predictive maintenance.
Fleet tracking, route optimisation and supply-chain visibility.
Document, matter and billing data engineered for search, reporting and AI-assisted review.
Product, usage and billing data pipelines for in-app analytics, metrics and customer reporting.
Governed enterprise data warehouses and KPI reporting across departments and regions.
§ Contact
Tell us about your sources, platforms and goals. We will suggest a practical next step, from an assessment to a full build.
