From Xander to FTSE 100 global insurance transformation.

How Software Engineer Associate Renuka transformed a global insurance company's automated data ingestion pipeline.

Renuka helped a global insurance company, who employ 50,000 people across 120 countries, to develop an automated data ingestion pipeline.


Working alongside the Senior Data Engineer, Renuka was tasked with developing a pipeline infrastructure to adapt to the client's newly developed system that utilises Python and Spark, whilst assisting the operations department with data validation from high-net-worth clients.

The Challenge

The client had the following challenges:

  • Efficiency issues

With such a large subscriber base, one of the main challenges the client faced was the sheer magnitude of datasets, meaning running scripts would take significant periods of time.

  • Data-informed stakeholders

Different stakeholders within the business needed data to make informed decisions, a process that involved manipulating and building large datasets and evaluating and presenting the results to the wider team.

  • Customer attraction

The client wanted to know how they could target their campaigns to the appropriate customers and increase engagements using historical data. This would need to be done by creating machine learning models using extremely large volumes of data.


The Solution

Renuka worked across multiple departments to provide specialist coding and data transformation skills.


Automate data processes

Support the operations department to automate their lengthy data validation procedure which required several iterations of reviews across various teams.


Python code development

Develop the necessary configuration and Python code to produce load-ready files within seconds to combat the lengthy data validation processes.


Senior engineer support

Provide critical python skills to a senior engineer from an adjacent department on a time-critical project to write a script to perform specific UI actions. 

The Outcome

1. Increased Efficiency 

Renuka reduced the time taken for ingesting complex data, which typically took over a week, to just under a few seconds.

2. Improved Customer Experience

Her Python code skills addressed a skills gap in a different department and helped transform the customer's user experience. 

3. Modernised Processes

The client's legacy processes, which were in place for seven years, were transferred by Renuka to an environment using Spark and Python, creating an efficient ingestion process across the whole organisation.

"Renuka has not only delivered this work to a high standard but has also built on and improved the existing framework from her knowledge and experience working with Python. She has been instrumental in improving a previously time consuming and laborious process."

Senior Data Engineer

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