A best in class technology business powering advanced competitive intelligence. With numerous patented ML algorithims in production and having come off a Q4 that saw them win numerous awards for best in class marketing performance this organisation is one not to miss out on!
Partnered with the likes of Marks & Spencer’s, Volkswagen and Qantas Airways to name just a few of their blue-chip clients, the business has spent the last decade building a fantastic data-driven culture with regular hackathons, and social events and even a technical mentor assigned to you when you first join to allow you to focus on developing across various areas of interest across the technology space.
Progression and retention is excellent across the business with members of the team staying put for numerous years and driving a particularly data-driven culture with regular opportunity for upskilling and progression. The work environment is predominantly remote, with the team spread across Europe, with a London based office available and travel onsite expected roughly once a month for social events.
The Role:
Joining an award winning data Engineering team, you will be tasked with working across a vast data team of around 40 individuals in order to utilise best in class software engineering practices in relation to functional programming. The data team is dealing with around 3 trillion data points every day, generated from over two thousand data processes running through workflows, huge distributed computations in spark, and streaming data coming in twenty-four hours a day at hundreds of times a second.
As a Data Engineer in this high-performing team you will be working across their entire stack, whether that’s writing innovative code in Spark for data processing and pipeline or working as part of an agile team utilising Scala and Spark to monitor and improve data processes, this is a data engineering role with serious variety behind it.
The successful candidate will possess the following skills and experience:
- A minimum of 2 years commercial experience working with Scala and/or Java.
- Commercial experience working with Spark
- Experience building ETL pipelines
- Experience using messaging technologies (Kafka etc)
- Be experienced in taking technical solutions and and explaining them to a less technical audience.
- Commercial experience working across the AWS tech-stack
Job Owner: guy.williams
