Data Engineer

Location London
Job type: SEED - Permanent
Salary: £DOE

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Our client is a global B2B travel company built on cutting-edge technology from day one!

As a member of the Data Engineering team, you will address complex and essential challenges by utilising advanced data technologies. As a member of the agile development team, you will contribute to the cloud-based data platform, ensuring its dynamic scalability and reliable operation. 

Developed products provide deep insights into travel programs, finances, and operations for internal and external clients. Every day, the data science team will utilise the platform you create to train and deploy machine learning models.

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What You’ll Do:

  • Writing code is in Python, Java, Scala, Spark, and SQL. Our client welcome programmers of all backgrounds as long as you focus on data engineering solutions and attention to quality.

  • Foster and strengthen a deep understanding of vast data sources in the cloud and know precisely how, when, and which data to use to solve particular business problems.

  • Design, architect, implement and support critical streams and datasets that support our business, clients, and data scientists.

  • Responsible for designing and implementing an end-to-end data solution, including data modelling, pipelining, transformation, and visualization. 

  • Work with product owners, operations and finance teams, and other data engineers to implement features benefitting the clients.

  • Be responsible for implementing best practices like infrastructure as code, automated testing, and code reviews.

The ideal candidate will have:

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  • Bachelor’s/Master’s Degree in Computer science, mathematics, statistics, economics, or other quantitative fields.

  • Experience as a Data Engineer or in a similar role.

  • Demonstrable experience with any programming or scripting language (Python/Java/Scala/Ruby etc.).’

  • Experience using big data technologies (Spark, Presto, etc.)

  • Experience using cloud technologies such as EMR, Lambda, EC2, and data pipelines.

  • Experience leading data warehousing and analytics projects, including using technologies such as Airflow, Jenkins, Snowflake, and Kinesis. 

  • Experience with Agile, DevOps, and CICD frameworks in cloud-based environments. 

  • Exposure to at least one dashboarding tool like Tableau, Power BI, Sisense, etc.