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hace 1 semana
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dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First.
Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail - one of the world's most competitive markets, with a deluge of multi-dimensional data - dunnhumby today enables businesses all over the world, across industries, to be Customer First. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Meijer, Procter & Gamble and Metro. We are looking for a talented Data Engineer to execute big data projects to create ready-to-use science products or software modules, engineering dunnhumby science into automated and scalable solutions available to capabilities teams. Developing the big data back-end for science products and reusable science modules, ensuring they are productionised and available to the business and keeping in mind that developed solutions have to distil complex problems into compelling insights that resonate with clients. Working with senior data science engineers to conduct requirements analysis and design the solution. Input into reengineering and design based on own expertise and implement advice from colleagues to resolve challenges and create big data back-ends for highly performant Business Intelligence applications for desktop platforms. What are we expecting from you- Bachelor's degree or equivalent in an engineering/numerate subject e.g. Engineering, Stats, Math, Computer Science.
- Experience with and passion for building back-end workflows and applications using modern technologies, and an appetite for understanding and implementing data science algorithms.
- Quick learner as some components of the tech stack could change.
- Backend stack: Python, Pyspark, Postgres, SQL, GCP, Linux, Docker.
- Strong programming skills in Python (including OOP).
- At least 2 years of back-end development using Pyspark, HDFS, Hive, any cloud platform.
- Good knowledge of SQL (joins, subqueries, etc.) and optimization techniques.
- Knowledge of general software design, architecture and best practices.
- Advanced English proficiency.
