Practice · Data & Databricks
Data platforms & Databricks
Data-engineering and Databricks consulting is the work of building a modern data platform your organisation can trust — assessing the estate, designing a governed Lakehouse, engineering reliable pipelines, and opening the data up to analytics and AI.
Strategys supplies the senior data engineers and Databricks specialists who do that work — as a project team or embedded in yours — for organisations that need the data to be right.
Who it's for
For organisations that run on their data
The organisations that get the most from a modern data platform are the ones where the data feeds decisions that matter — regulated reporting, research, operations. They share one constraint: the platform has to be governed and the numbers have to be right.
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Financial services
Banks and insurers consolidating risk, regulatory, actuarial and analytics workloads onto one governed platform under DORA operational-resilience scrutiny.
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Life sciences
Pharma and biotech organisations engineering research, omics and clinical data pipelines that have to hold up in regulated environments.
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Public sector & industry
Agencies and manufacturers modernising analytics and operational data onto open, auditable foundations they can own in-house.
How we work
A platform you can trust and own
We build the platform in layers, with governance designed in from the start rather than added later. Where the starting point is a legacy SAS estate, the same practice covers the move across — see our dedicated SAS to Databricks migration page for how we keep regulated reporting exact through the change.
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Assess the data estate
Map the sources, pipelines, consumers and pain points, and agree what the platform has to deliver — for analytics, reporting and AI — before any build begins.
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Design the Lakehouse
Design a target architecture on the Databricks Lakehouse: layered data (bronze/silver/gold), governance and access model, and how it fits your cloud and existing tools.
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Engineer the pipelines
Build reliable, tested data-engineering pipelines in Spark SQL and Python — batch and streaming — with quality checks so downstream users can trust the data.
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Govern and secure
Put cataloguing, lineage, access control and cost management in place so the platform is secure, auditable and affordable to run as it grows.
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Enable analytics and AI
Open the governed data up to BI, analytics and machine learning, and upskill your team so the platform is owned in-house, not left dependent on us.
Experience
Senior data engineers, not a training ground
Every consultant we place on a data engagement is a senior specialist with hands-on data-engineering and Databricks experience. We work across financial services, life sciences, the public sector and manufacturing, with senior specialists who bring both Danish and international experience. Governed data is also the foundation for our AI and generative-AI work.
FAQ
Data & Databricks — questions we get
What does a Databricks consultant do?
A Databricks consultant designs and builds data platforms on the Databricks Lakehouse and the data-engineering pipelines that feed them. In practice that means assessing your data estate, designing the target architecture, engineering tested pipelines in Spark SQL and Python, putting governance and security in place, and enabling analytics and AI on top — then handing it over so your team can run it.
What is the Databricks Lakehouse?
The Lakehouse is an architecture that combines the low cost and flexibility of a data lake with the reliability and performance of a data warehouse on one platform. It lets data engineering, analytics and AI run against the same governed data, which is why organisations consolidate onto it rather than maintaining separate systems.
Do you also handle SAS to Databricks migration?
Yes. SAS to Databricks migration is a specialist part of this practice, common in banking, insurance and the public sector where the heaviest SAS estates sit. We have a dedicated page on how we assess, convert and validate SAS workloads onto Databricks without breaking regulated reporting.
Which cloud do you build Databricks on?
Databricks runs on the major clouds, and we work to the platform your organisation has chosen. The Lakehouse design, pipelines and governance patterns we use are broadly consistent across clouds, so the approach does not change with the underlying provider.
How do you make sure the data platform is trustworthy and governed?
We design governance in from the start — data quality checks in the pipelines, cataloguing and lineage so people can find and trust data, access control so the right people see the right data, and cost management so it stays affordable. For regulated clients this is the difference between a platform that passes audit and one that does not.
Can Strategys work as embedded specialists or as a full project team?
Both. We supply senior data engineers and Databricks specialists either embedded in your team as staff augmentation, or as a project team that owns delivery end to end, across Denmark and the Nordics in Danish, English, Arabic, Urdu and other European languages.
Building or modernising a data platform?
Tell us about your data estate and what it has to deliver. We will talk you through how a governed Databricks Lakehouse would work for your organisation.
Contact us