Strength in numbers
What is data engineering?
Transforming tremendous amounts of business data into useful insights. Setting the stage for detailed business analytics and in-depth business insights. Data engineering is all about developing, testing, and maintaining data pipelines. Our data engineers work on modeling actual databases, determining what exactly they will look like.
Get in touch
We’re here to find fast, elegant solutions to your trickiest problems.
Book a callMoving past limits. Going somewhere new.
Proactive. Expert. Passionate. We’ve worked on a multitude of projects across Europe, the UAE, and the USA. Many of our clients have been working side by side with us as their technical partners. That means we’ve built up a huge amount of expertise across various industries.
We are your technical partner, co-creating your digital products and helping you transform business data into invaluable insights.
Get in touchEnd-to-end data engineering
As your technical partner, we build custom-tailored solutions, designed to meet your specific business requirements. We create flexible and scalable data warehouses, build strong data pipelines, and implement cutting-edge data analytics solutions.
Data pipelines
ML engineering
Data transformation
DataOps
Harness the power of data. Future-proof your business.
Collaborative. Client-centric. Results-driven. We have worked with clients across various industries and, along the way, gained strong domain experience. FinTech. InsurTech. EdTech. HealthTech. Retail. And, along the way, we’ve gathered a heap of domain expertise in various sectors.
As your data engineering partner, we focus on addressing your unique challenges and opportunities, delivering custom solutions for you.
What we have done for our customers
Our work
Which business model suits you?
Different budgets, deadlines, challenges, and requirements. There is no one-size-fits-all approach to software development. To match your exact goals and ambitions, we offer two types of business models:
- Time & material: Greater control. Flexibility. Participation in candidate selection. With no rigid processes or end dates, this business model is easier to scale up or down as your business needs change.
- Fixed price: Fixed scope. Fixed budget. Fixed timeline. Those are the main benefits of the fixed price model. You set the requirements upfront, and we deliver the project within them.
Many clients choose to start with the fixed-price model. However, as their project scope evolves, they typically shift to the time & material model.
Our tech stack: designed to work with yours
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ETL
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Python
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PySpark
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Kafka
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Hadoop
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Apache Airflow
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NLP
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Machine Learning
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Data Mining
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Pandas
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Keras
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Power BI
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Azure Synapse Analytics
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SQL
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Excel
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NoSQL
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Data Analysis
Richard’s relentless passion for innovation delivers digital, commercial and organisational growth for our clients. He joins Vega IT from IBM where he was an Executive Partner shaping digital change programmes. As a multi-award-winning digital business transformation consultant with 30 years of experience, he’s highly experienced at helping organisations define and deliver their technology enabled transformation programmes.
Richard Morris
Executive PartnerSend us your contact details and a brief outline of what you might need, and we’ll be in touch within 12 hours.
Data Engineering - FAQ
Data engineering is a data science area, focused on building end-to-end systems that enable the collection and usage of massive amounts of business data.
By investing in data engineering, you will make better decisions based on the insights you gain from your multi-source business data. This helps you improve the quality of your services, minimize costs, and reduce project duration. That way, you will better meet your customers’ needs and make wiser business decisions.
We have vast experience in the field of data engineering, including:
- Data integration
- Data transformation
- Data warehousing
- Data modeling
- ETL pipelines
- Data quality management
- Data governance
- Big data management
- Data security
- Cloud data engineering
Identifying the client’s needs
Creating a highly scalable efficient data solution
Utilizing ETL processes
Assessing data quality
Building an end-to-end solution for your company