Data isn’t useful until it’s structured, validated, and accessible. Without the right systems, you’re stuck with fragmented data, manual reports, and costly compliance risks. Our data engineering services convert raw datasets into analysis-ready, compliant, and scalable information pipelines.
From GDPR-compliant data lakes for healthcare providers to ETL pipelines that keep e-commerce stock levels up to date, we design data solutions that fit the unique demands of UK businesses. Our approach ensures your data is usable, secure, and always ready for analysis. Need actionable data without delays or errors? We make it happen.
The 4 Core Components of Data Engineering
- Data Extraction – Pull raw data from CRMs, ERPs, and third-party APIs.
- Data Transformation – Standardise, clean, and validate it to meet your business logic.
- Data Storage – Store data in a secure data warehouse or data lake for long-term use.
- Data Delivery – Route clean data to reporting tools like Tableau, Power BI, and Looker.
Industry-Specific Data Engineering Solutions
No two industries work the same way, and neither should their data systems. Our approach to data engineering services is shaped by industry-specific regulations, operational pain points, and customer expectations. We understand that financial services require FCA compliance, healthcare needs GDPR-compliant patient records, and e-commerce must track real-time stock availability.
Data Engineering for Financial Services
The financial sector runs on precision and compliance. We build FCA-compliant data pipelines that support risk management, fraud detection, and customer data privacy.
Example Use Case:
A UK-based payments provider wanted to detect fraud faster. We built a real-time alert system powered by ETL pipelines and anomaly detection algorithms. The result? Fraud detection times dropped from 2 hours to 15 minutes.
Data Engineering for Retail & E-Commerce
Speed and accuracy are crucial for retail and e-commerce brands. Our data solutions keep stock levels accurate, build real-time sales dashboards, and track customer activity in real-time.
Example Use Case:
A fashion retailer struggled with overselling during Black Friday. We built a real-time stock tracking system that updated availability every 5 minutes. As a result, the business avoided overselling and maintained customer trust during peak sales.
Data Engineering for Healthcare Providers
The healthcare sector handles large datasets that require encryption, validation, and secure access. We design GDPR-compliant patient record systems and encrypted data lakes for secure data storage.
Example Use Case:
A UK healthcare provider needed a way to track patient data without violating GDPR. We built a role-based access control (RBAC) system that restricted access to sensitive data, ensuring only authorised healthcare professionals could view it.
Data Engineering Services We Provide
We don’t offer off-the-shelf solutions. Instead, we provide custom data engineering services that solve the specific challenges your business faces. Our technical scope includes the following core services:
Data Pipelines & ETL (Extract, Transform, Load)
Data doesn’t move itself. We create ETL pipelines that automate the flow of information from CRMs, ERPs, and third-party APIs into centralised systems. This eliminates manual work and errors.
Technologies: Apache Airflow, AWS Glue, Python, SQL
Example Use Case:
An e-commerce retailer had 10+ data sources feeding into a dashboard, but manual exports were slowing them down. We built a unified ETL pipeline to sync sales, inventory, and marketing data into one place — no manual work required.
Data Lakes & Data Warehouses
We build data lakes (for raw data) and data warehouses (for structured, analysis-ready data) using tools like AWS S3, Snowflake, and Redshift. This allows you to store data in a way that’s accessible, secure, and fast.
Example Use Case:
A fintech firm required a data warehouse that could query millions of transactions. We built a Snowflake warehouse that ran queries in 8 seconds instead of 2 hours.
Data Governance & GDPR Compliance
GDPR isn’t optional. We design frameworks for data encryption, access control, and compliance tracking to ensure you meet GDPR, ICO, and FCA regulations.
Example Use Case:
A healthcare client needed to protect sensitive patient records. We built an encrypted data lake and implemented role-based access to ensure only doctors could access certain files.
Cloud Data Migration (AWS, Azure, GCP)
Switching from on-premise to the cloud? We offer seamless data migration to AWS, Azure, and Google Cloud. All data is validated before and after migration.
Example Use Case:
A UK insurance firm migrated 10TB of legacy data to AWS. We achieved 100% data integrity with zero downtime, allowing for a seamless shift to a more scalable system.
Our 5-Step Data Engineering Process
Our process keeps risk low and performance high. Here’s how we execute data engineering projects from start to finish:
1️ Discovery – We audit your existing data and define the business requirements.
2️⃣ Data Architecture Design – Build the architecture (e.g., data lake, warehouse) for efficient storage.
3️⃣ Development & Integration – Develop ETL pipelines, data models, and APIs.
4️⃣ Testing & Compliance Checks – Conduct testing to ensure GDPR compliance and data accuracy.
5️⃣ Ongoing Support – We maintain your system, optimise pipelines, and offer 24/7 support.
Why Companies Choose Us for Data Engineering
We understand what matters most to UK businesses. From GDPR compliance to FCA-regulated financial data, we meet the highest standards of security, speed, and precision.
- Full GDPR Compliance – Your data systems are designed with GDPR, FCA, and ICO rules in mind.
- Custom-Built Systems – We create solutions from scratch, not recycled templates.
- Data Accuracy Guarantee – No data duplication, no missed data. Every dataset is checked.
- Direct Access to Engineers – No outsourced support. Speak directly with our UK-based engineers.
Technical FAQs (For IT, CTOs, and Data Teams)
A data warehouse holds structured data that’s ready for analysis, while a data lake stores raw, unstructured data.
We encrypt data at rest, apply role-based access control (RBAC), and log every action for GDPR audits.
We use Apache Airflow, AWS Glue, Python, and dbt to create automated data pipelines.
Timelines depend on scope, but most projects take 2-12 weeks.
We handle the end-to-end process: planning, transfer, and validation to ensure no data loss.
Is Your Data Infrastructure Holding You Back? Let's Fix It Before It Breaks.
Data issues won’t fix themselves. If broken dashboards, data duplication, or compliance risks are slowing you down, you’re already losing ground.
Don’t let these challenges stifle your growth. Speak with a Data Engineering specialist to optimize your data architecture, eliminate redundancies, and ensure compliance, so you can scale faster and make data-driven decisions with confidence.