Design, build, migrate and optimise Snowflake with an official Snowflake partner.
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§ Signs
As an official Snowflake partner, we help teams design, build and run Snowflake data warehouses that stay fast and affordable as they grow. Our Snowflake data engineers handle architecture, ELT pipelines with Snowpipe, Streams, Tasks and Dynamic Tables, SQL development and query tuning, and dbt transformations. We migrate SQL Server and legacy warehouses to Snowflake, set up RBAC, governance and secure data sharing, and connect Snowflake to Azure, AWS and your BI platforms. When an account has grown slow or expensive, we tune warehouses, queries and resource monitors to bring performance and credit use back under control.
Snowflake is easy to start and easy to let drift. These are the patterns we see most often when teams call us.
Credit consumption rises every month, yet nobody can say which warehouse, team or query is responsible.
Loading, dbt runs and dashboards share the same compute, so reports slow down whenever a large load starts.
Daily work runs under ACCOUNTADMIN, grants are copied from user to user and no one owns the sensitive columns.
The old SQL Server or legacy warehouse still runs in parallel because nobody trusts the reconciliation.
Stored procedures and scheduled tasks with no tests, no version control and no documentation.
Partners and customers receive CSV extracts by email or SFTP instead of governed, live shares.
§ What we deliver
Choose an area to see the services in it.
AWS
dbt§ Proof
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§ Approach
We review your Snowflake account or source systems: workloads, data volumes, query history and spend.
You receive Snowflake assessment with performance and cost findings
We design databases, schemas, warehouses, roles and naming standards for your workloads.
You receive Target architecture and RBAC model
ELT pipelines, Snowpipe ingestion, Streams and Tasks, and dbt models, built and tested in version control.
You receive Tested pipelines and dbt models in your repository
Data and SQL code are moved in waves, with incremental loads during the transition and row-level reconciliation.
You receive Reconciliation reports and a cut-over plan
We tune queries, warehouse sizes and clustering, and set resource monitors so cost stays predictable.
You receive Cost and performance report with resource monitors in place
We document the platform, walk your team through it and agree whether you run it alone, with periodic reviews or with our managed support.
You receive Runbooks, cost dashboards and an agreed support option
§ Tech stack
dbt
Azure Data FactoryAWS
Power BI§ 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
Designs the warehouse and its security model, builds ELT pipelines with Snowpipe, Streams, Tasks and Dynamic Tables, writes and tunes SQL, implements dbt transformations, and integrates Snowflake with Azure, AWS and BI platforms.
Yes. SQL Server to Snowflake migration is one of our specialised consulting services: schema and code conversion, data movement, incremental loads during the transition, and reconciliation against the source before cut-over.
By right-sizing warehouses and auto-suspend settings, separating workloads, tuning expensive queries, choosing the right materialisations and setting resource monitors, so credit use is visible and controlled.
Yes. We build dbt transformations on Snowflake with tests, documentation and lineage, deployed through Git-based CI/CD.
Yes. We set up Snowflake data sharing and secure data collaboration, with access governed by roles and policies rather than file exports.
Yes. Equitysoft is an official Snowflake partner.
It depends on the number of sources, the volume of legacy code and how much governance work is needed. An assessment takes a few weeks, and the first production pipelines usually follow soon after. We give you a phased plan once we have seen your estate, rather than a guess up front.
Snowflake suits SQL-centreed warehousing, BI and data sharing with very little platform administration. Databricks suits Spark-heavy engineering, streaming and machine learning on open table formats. Many companies run both. We partner with both, so we recommend based on your workloads, not on a sales target.
Yes. We use Snowpark for Python transformations, UDFs and feature preparation that run inside Snowflake, so data does not have to leave the platform to be processed.
Yes, most of our Snowflake work starts in an existing account. We begin with a read-only review of query history, warehouse settings and role grants before changing anything.
Least-privilege roles, SSO and MFA, network policies, masking and row access policies, object tagging and regular access-history reviews. We work under NDA, inside your account, and design controls around your UK GDPR and Data Protection Act 2018 obligations.
Well-defined work such as an assessment or the migration of a known estate can be fixed price. Evolving roadmaps suit time and materials or dedicated engineers. After a first call we send a written estimate with the assumptions behind it.
§ In detail
Databases, schemas, environments, warehouses per workload and naming standards, written down so new teams follow the same pattern.
Functional and access roles, masking and row access policies, and object tags that mark sensitive data.
Snowpipe, Streams and Tasks or Dynamic Tables, and a dbt project with tests, all in your Git repository.
Resource monitors, auto-suspend settings and a query-level cost view that maps credits to teams and workloads.
Reconciliation results per table, a cut-over checklist and a rollback plan signed off before the switch.
How to add a source, onboard a user, rotate a key and respond to a failed load.
We build inside your Snowflake account and your Git. No proprietary layer sits between you and your data.
Architecture choices are captured as short decision records your engineers can review before we build.
We pair with your engineers on the first pipelines so they can extend the pattern without us.
Take full ownership, keep us for a periodic cost and performance review, or move to managed support.
Secure data sharing with partners, masking for account and card data, and access history you can show an auditor.
Orders, inventory and marketing data in one place, with Snowpipe keeping trading views close to real time.
Tag-based policies keep identifiable fields restricted, with access design shaped around UK GDPR and the Data Protection Act 2018.
Product usage data for customer-facing analytics, and per-customer shares instead of scheduled exports.
§ Contact
Planning a new Snowflake platform, a migration, or a cost review? Tell us where you are and we will suggest the next step.
