Software development as a service
Senior developers who join your team for as long as you need them. No recruitment fees and no months spent getting up to speed.
Data engineering and AI
Numbers your whole company agrees on
We build the pipelines, lakehouses and reports that turn scattered spreadsheets and databases into one reliable source of truth. Our team holds Databricks platform architect accreditation and has spent years working with financial data, where a wrong figure is never a small problem.
Sound familiar?
Signs your data needs attention
If two or three of these ring true, a short conversation will probably save you money.
- Closing the month means days of copying between spreadsheets.
- Two departments bring different numbers to the same meeting.
- The data warehouse bill keeps rising and nobody can say exactly why.
- Reports break whenever someone changes a source system.
- An auditor asks where a figure came from and it takes a week to answer.
- You want to try AI, but your data sits in a dozen places that do not talk to each other.
What we do
From raw data to decisions
We can take on the whole platform or one stubborn piece of it. Either way you get something your own people can understand and maintain.
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Data platform design
A lakehouse on Databricks, or on the platform you already pay for, with clear layers for raw, cleaned and trusted data, and a sensible structure for who can see what.
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Pipelines and integration
Reliable feeds from your CRM, trading platform, ERP, payment providers and external APIs, with automatic checks that stop bad data before it reaches a report.
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Reporting and dashboards
Power BI, Databricks SQL or whatever your team already uses, built on definitions agreed with the business so a customer, a trade or a sale means the same thing everywhere.
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Migration and cost control
Moving off ageing database servers or an overgrown warehouse, and tuning clusters and jobs so the monthly bill finally makes sense.
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Getting ready for AI
Clean data with clear ownership, and the access controls you need before anyone builds a forecast, a chatbot or a model on top of it. When the foundations are in place, we help you ship the first AI feature that is actually useful.
How it works
A typical data engagement
We prefer to prove value early. The first useful report usually arrives within weeks, not at the end of a long programme.
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Data review
We map your sources, how data moves today and where it goes wrong. You get a short written report and a proposed architecture with rough costs.
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First data product
We pick one report or dataset that really matters and build it properly, all the way from source systems to the screen people use.
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Scale out
With the patterns proven, we bring in the remaining sources, automate testing and deployment, and set up monitoring and cost alerts.
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Handover or support
Your team takes over with documentation and training, or we stay on to run and improve the platform. Many clients choose a mix of both.
For technical readersPlatforms, tools and practices we use for data work
Platforms
Languages and frameworks
Practices
Medallion architecture with bronze, silver and gold layers. Data quality expectations on every pipeline. Infrastructure as code with Terraform and Databricks Asset Bundles, deployed through CI pipelines. Access by role, column masking for personal data, lineage through Unity Catalog, and cost monitoring per workload.
More on how we work across all projects is on our technology and standards page.
Questions
Common questions
Anything else? Email info@avientiq.com and one of our engineers will reply.
Do we actually need Databricks?
Not always. For modest data volumes a carefully designed PostgreSQL or Azure SQL setup is often cheaper and easier to run. We recommend Databricks when the volume, the variety of sources or your AI plans justify it, and we will tell you plainly if they do not.
Can you work with our existing data team?
Yes. Some clients want us to build the platform and train their analysts to run it. Others want an extra senior engineer inside the team for a few months. Both work well.
How do you handle sensitive or regulated data?
Access is granted by role, data is encrypted at rest and in transit, and personal data is masked outside production. Our engineers have worked under CySEC, FCA and GDPR requirements, and we document the things an auditor will ask about before they ask.
What does a first engagement cost?
Most clients start with a data review, which we price as a fixed fee agreed before we begin. It gives you a clear picture and a plan, and you are under no obligation to continue with us afterwards.
Related services
Often paired with this
Cloud and DevOps
Azure and AWS setups that are secure, automated and sensibly priced. We also tidy up the ones that grew by accident.
Digital consulting
An honest outside view of your technology. Architecture reviews, roadmaps and due diligence, written for the people who approve the budget.
Next step
Tell us what you're working on
Send a few lines about your project or the problem in front of you. We'll come back with honest questions, a rough plan and a sense of cost. No sales pitch unless you ask for one.