Data Engineering Services and Analytic Platforms

Securing the building blocks of data science

Establish a robust foundation

Modern technology platforms underpin data-driven transformation. Our data engineering services bridge the gap between data science and data strategy – ensuring access to the right data, at the right time, in the right format, for your advanced analytics to thrive.


Any data science team is only as good as its data engineers. And we have some of the best. Our specialists use a variety of modern data technologies and languages, like Python and R, to build scalable data workflows and APIs; collecting, storing and transforming data – even from legacy systems – for advanced analytics. From individual projects to company-wide transformation, we work closely with data scientists to integrate models into your operations and translate theory into results.


Uncover the potential of sharing data for convenience, simplicity and efficiency with RStudio. As a certified RStudio partner, we can streamline your development environment and accelerate adoption – giving your data science teams everything they need to exploit the potential of R at scale.

Find Out More

Where our data engineering services can add value:

  • Migrating legacy systems – to a modern platform that is efficient, robust and adheres to data governance for process improvement
  • Collecting, preparing and providing data – that data scientists can analyse and use to build predictive models
  • Integrating models – to ensure results are available within the enterprise’s suite of data tools
  • Setting up and administering data platforms – including databases, computation engines, visualisation tools, web servers and data visualisation apps
  • Implementing from proof of concept to production – in a cloud based environment

Our data engineers are adept in:

  • SQL – even if your data won’t be stored in a traditional RDMS, many modern systems (like Hive on Hadoop) still use a SQL interface.
  • Pipeline design – building efficient and easy-to-maintain ETL or ELT pipelines to move, transform and store data (including batch processing and data streaming).
  • Data modelling – building data warehouses that deliver what analysts need, aligned to data governance (including entity-relationship modelling, dimensional modelling, and metadata management).
  • Programming skills – to action all of the above into practice in a safe, robust way.
  • Multiple related specialisms – our data engineering team combines specialist knowledge from a wide variety of backgrounds, including database and data warehouse development, general software development, BI and data analytics through to DevOps engineering.


Explore the latest insights to inspire your next data science project.

data scientist or data engineer - what's the difference?


Data Scientist or Data Engineer – What’s the difference?

Author: Principal Consultant, Dean Wood When it was floated that I should write this article, I approached it with trepidation….

Mango Supports New development of ONS Data Science Campus

Case Study

Mango Chosen to Support Development of New ONS Data Science Campus

The Data Science Campus (the Campus) is part of the Office for National Statistics (ONS), which is the government’s National…

View All


Do you want to explore the power of data engineering and platforms? Contact us to arrange a no obligation meeting with our data science consultants.

Get in touch