Associate Data Engineer

Join Quantexa, a fast-growing scale-up in the UK, as an Associate Data Engineer. You will be part of the Applications team, focused on building real-world applications of the Quantexa Platform. Your role will involve developing libraries for data cleansing and standardization, building reusable code for processing data sets, maintaining demos, and contributing to the development of Quantexa's SaaS offering. You will have the opportunity to rotate between sub-teams for knowledge sharing and personal development. Benefits include a pension scheme, 25 days of annual leave, private healthcare, and more.

• Participer au développement des bibliothèques de Quantexa pour le nettoyage, l'analyse et la normalisation des données utilisées dans la résolution d'entités.
• Construire du code standardisé et réutilisable pour le traitement de divers ensembles de données tierces.
• Développer, déployer et maintenir toutes les démonstrations de Quantexa, en mettant en valeur les différents cas d'utilisation de la plateforme Quantexa.
• Analysing and examining real and varied data
• Growing and thriving within one of the UK’s fastest growing scale-ups
• Working in the cloud with production-grade systems
• Defining best-practices and sharing expertise you’ve developed
• Solving difficult problems with efficient, resilient, high impact code
• Data processing/ETL pipelines
• Working in a fast moving, Agile environment
• Full stack development, but with a heavy focus on the data processing/ETL side
• Big data, either from a software deployment/implementation or a data science perspective
• A strong coding background, ideally in Scala or otherwise in a relevant language that will allow you to learn Scala quickly (e.g. Java/Python)
• Working with big data technology, ideally Spark but others will also be useful such as Airflow or Elasticsearch
• Building data processing pipelines for use in production batch systems, including either traditional ETL pipelines and/or analytics pipelines
• Working in an Agile environment
• Manipulating data through cleansing, parsing, standardising etc, especially in relation to improving data quality/integrity
• Building and deploying SaaS products