Rapid implementation
We build modern, governed data platforms in weeks, not months, using our Seriös ONE DataOps framework to rapidly unify your data, strengthen governance and improve performance across Databricks, Snowflake and Microsoft Fabric.
Data Solutions
Data Engineering
Data Engineering That Accelerates Delivery
We specialise in data engineering, building data platforms and pipelines that move, transform and structure your organisation's data so it can drive insights, analytics, predictive intelligence and AI.
You get value from your organisation's data only when you can access it, understand it and use it. That’s why your data must be engineered effectively. We build governed, scalable data platforms that give you a trusted foundation and deliver tangible value within 8 weeks.
Seriös ONE, How We Engineer Data Solutions
Data engineering gives you the structure and automation needed to keep your data accurate, connected and accessible. With clean pipelines and a well‑designed architecture, your analytics become faster, more reliable and able to scale as your data and demands increase. Seriös ONE, our DataOps framework, accelerates this with rapid data unification and built‑in guardrails that deliver scalable and governed data solutions.
Automated data pipelines
Our data engineers build ETL and ELT pipelines that automate and orchestrate the movement of data across your ecosystem. From data ingestion to integration, every
pipeline is optimised for resilience, scalability and continuous delivery.
Data Transformation
We transform raw data into structured, governed formats using industry-standard modelling techniques like Medallion Architecture, Data Vault, and Kimball to ensure integrity from source to insight, making your data ready for analytics and AI.
Secure and Scalable Data Platforms
We can modernise and optimise your existing data platform so it’s secure, scalable and ready for growth. Whether you’re refining what you already have or moving to the cloud, we refactor pipelines, manage migrations and build solid data foundations that support your organisation's long‑term needs.
Our Data Solutions in Action
“The future of work is here. Though people are working in a hybrid manner, their desire for collaboration and offering exceptional workplace experiences is higher than ever. Our partnership with Seriös Group has enabled JLL to rise to this challenge through innovation in data and analytics.”
“Our partnership with Seriös Group has brought game-changing improvements to both our football performance and commercial operations. Through the power of integrated data, we're creating a smarter, more agile, and more engaged club.”
“By working with Seriös Group to establish best practices and implement Seriös ONE Launchpad, we’ve successfully transformed our data into a true strategic asset. With a unified and governed data platform, we can gain real-time insights, achieve a single view of our customers, and streamline our operations, allowing us to make smarter, faster decisions.”
“The flexible architecture of Seriös ONE Launchpad positions Equans for future growth, allowing the expansion of Condition Based Maintenance (CBM) to additional sites and integration of more data sources. The ongoing remote monitoring has meant quick identification and resolution of asset-related issues, extending the lifetime performance of the hospital's infrastructure while minimising carbon emissions.”
“Partnering with Seriös Group has proven to be a highly effective extension of our data capabilities. The flexibility and depth of expertise they offer has provided us with a reliable source of data support on tap, enabling us to scale and adapt quickly to evolving business needs.”
Strong Data Foundations Build Strong Organisations
With Seriös ONE, our DataOps framework, we build the unified, governed data foundations your organisation needs. It accelerates your data engineering processes by using metadata defined by your team to automate repetitive tasks, reduce manual effort and enforce consistency. This improves data quality, reduces cost and speeds up delivery, freeing your data teams to focus on high‑value work.
Who Needs Data Engineering?
If you’re dealing with fragmented data, inconsistent formats or manual reporting processes, data engineering gives you the structure and automation you need. It connects your sources, standardises how data is processed and ensures it flows reliably across your organisation. With Seriös ONE, our DataOps framework, we unify your data faster and apply built‑in guardrails that keep everything governed, scalable and aligned to best practice. By automating ETL pipelines and structuring your data for analytics, you get accurate, timely insights that improve data quality, reduce manual effort and means your organisation can make data informed decisions.
Data Engineering Built for Your Environment
Your tech stack needs to be the right one for your organisation. Whether you use Azure, AWS or GCP, we build data platforms that fit your infrastructure and specialise in a core set of technologies proven to deliver results quickly.
Why Seriös Group
We aim for every engagement with our Data Solutions Experts to create lasting impact for your data team and your organisation.
Speed to Value
Our DataOps framework, Seriös ONE delivers value early by accelerating your data engineering processes without compromising quality. You move quickly from strategy to delivery and see results fast.
Integrity in Every Layer
We work transparently and collaboratively, acting as an extension of your team to make your data systems practical and sustainable.
Precision in Every Build
We engineer with purpose: reliable pipelines, efficient storage and cloud-native architectures built for performance and adaptability.
Excellence Through Innovation
We continually refine, automate and evolve our solutions, helping your data platforms stay ahead of business needs and emerging technology.
How ready is your organisation for AI?
Our 10‑step Data Readiness for AI framework shows whether your data foundations are strong enough for AI, and what you need to build first to make AI viable.
Frequently Asked Questions
Got questions? We’ve got answers...
How does data engineering improve data management and analytics?
Data engineering builds the foundation for trusted data. It captures, cleans, organises and automates the flow of data from source to impact; ensuring it is accurate, timely and fit for purpose. Well-engineered pipelines reduce manual effort, improve reliability and deliver the right data to the right people in the right format. By applying consistent structure, monitoring and automation, data engineering strengthens data quality, supports governance, enables faster reporting and ensures analytics and AI models run on consistent, secure and connected data.
What problems does data engineering solve for Data Leaders?
Data engineering removes the structural blockers that hold data leaders back by breaking down silos, reducing manual effort and building a foundation for trusted, well-governed data. It enables clear ownership and scalable governance through lineage, quality checks and access controls, while supporting secure self-service, data marts and domain-driven delivery. By connecting and standardising data across systems, it turns fragmented assets into a coherent data platform. This improves access to insight, accelerates innovation and helps data leaders maximise the return on data as an asset while moving from reactive reporting to proactive decision-making.
What does 'good' look like in data engineering?
Good data engineering delivers trusted, well-structured data through pipelines that are automated, testable and scalable. It includes built-in quality checks, lineage, monitoring and orchestration, with clear separation of code and config aligned to CI/CD and governance standards. Security is embedded through Zero Trust principles, and cost-efficiency is considered from the outset to support FinOps goals and sustainable scaling. This creates a high-trust, low-friction environment where teams can access reliable data in the right format at the right time, enabling faster decisions, lower risk and greater return on data investment.
How does data engineering maximise the value of our data assets?
Effective data engineering maximises the value of data by making it accessible, trusted and fit for purpose across the organisation, from operational reporting to advanced analytics and AI. It enables scalable, real-time pipelines that integrate structured and unstructured data, reduce latency and improve the speed, efficiency and reliability of decision-making. By embedding governance, data quality, lineage and access controls into pipeline design, it strengthens compliance, reduces risk and supports consistent, auditable use of data. Cost-efficiency is also achieved by designing for scale, reducing duplication and enabling automation across data flows and decision workflows. This foundation turns data from a fragmented resource into a strategic asset that can be shared, reused and applied to high-impact initiatives.
What’s the difference between a data warehouse and a data platform?
A data warehouse stores structured, organised information ready for reporting and analysis, while a data platform is the complete environment that connects storage, pipelines, governance, and processing of your organisation's data. Its a more modern and scalable cloud, that can cope with future demands.
How do you ensure the security and compliance of data pipelines?
We embed security and compliance into every stage of data engineering. Our pipelines are built with governance controls, encryption, and access management that can support your organisation in meeting GDPR obligations and achieving compliance with standards like ISO 27001 and SOC 2. While these frameworks don’t prescribe how to build data pipelines, the controls we implement provide the evidence and assurance needed for audits, keeping your data protected, traceable, and trusted from source to insight.