Big Data Engineer (Scala, Spark + AWS)
Athens, Greece
πριν από 10 ώρες
source : Just Join IT


Successfully cooperating with our client helping people move forward with credit, providing products that responsibly meet their needs.

Whether this is offering new ways of accessing credit with a leading retailer or providing tools to facilitate customers’ management of their accounts, client will continuously strive to help customers responsibly make the most of their credit.

We offer an approach to financial services that is in touch with people and their lives. It is an approach grounded in customer knowledge and differentiated by our passion to deliver the products, services, tools and expertise that best meet our customers’ needs.

Currently we are looking for a Middle Big Data Engineer to make our team even stronger.


  • Proficient in Big Data integration technologies such as : Spark, Scala, AWS Data Pipeline for orchestration, Dremio, Glue, AWS Athena, AWS S3, EMR
  • Excellent with API and library design skills
  • Proficient with traditional database SQL technologies (Oracle, SQL Server, DB2)
  • Having pracctice with integration of data from multiple data sources
  • Able to write high-performance, reliable and maintainable code
  • Pretty knowledgeable of NoSQL database structures theories, principles, and practices
  • Confident in CI / CD best practice, multi-threading and concurrency concepts
  • Accustomed to cloud deployment
  • Familiar with the fundamentals of Linux scripting language
  • Nice-to-have skills :

  • Python
  • Building applications for cloud environment

  • Modeling, manipulation, transformation, and loading of the Data Lake technology layers
  • Designing and coding of data transformation and loading processes through the various layers of the Data Lake using Big Data open-source technologies such as Kafka, Spark, Scala, and associated AWS ETL tooling
  • Owning all of the Data Content, manipulation, business rules, and associated processes within the Data Lake
  • Champion quality and simplicity in the system code and leading the enforcement to quality within the data landscape
  • Us according to Agile approach
  • Monitoring and profiling performance and suggesting / implementing solutions where appropriate
  • Recommending and testing new data structures, and physical data layouts, to improve throughput and performance
  • Championing the new Data Lake technology across the organization to address a broad set of use cases across data science and data warehousing
  • Researching, testing, and recommending new layers or products in the Data Lake stack as these fast-moving technologies develop, keeping Client at the forefront able to attract the best talent
  • Educating and training other resources in the organization whenever needed

  • Model, manipulate, transform and load Data Lake technology layers. Build knowledge of all data resources within Client and prototype new data sources internally and external to Client
  • Building knowledge of all existing data manipulation within both data warehouse systems and within the business marts
  • Design and code data transformation and load processes through the various layers of the Data Lake
  • Get a great deal of learning and development opportunities along with our structured career path
  • Process dynamic projects and still have a stable place of work
  • Take part in internal and external events where you can build and promote your personal brand
  • Work with experienced specialists willing to share their knowledge
  • Care about your individual initiatives we are open for them, just come and share your ideas
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