DATA ENGINEER - Gothenburg

Veritaz is a fast-growing IT-consultant firm. Our company is made up of insanely bright people from over 4 countries, and we are located in Sweden, UK, US and Pakistan. The voyage has been incredible this far, but it is only the beginning.

Assignment Description:

We are looking for a Data Engineer who is experienced in Data modelling and DI tools and is interested to be part of a multi-platform agile solutions environment.

Do you value openness, transparency, and empowerment? Our squad is high performing cross-functional team who are set with a mission to provide win-win exchanges for our customers.

What you'll do:

● Setting technical direction as well as creating and maintaining optimal data pipeline architecture.

● Work in a multi-functional agile team to assemble large, complex data sets that meet functional / non-functional business requirements.

● Work with state-of-the-art data processing frameworks, technologies, and cloud platforms.

● Help drive optimization, testing, and tooling to improve data quality, and be an active member of the Data Engineering community and collaborate with other Engineers across the cluster.

● Increase developer productivity by building innovative tools that reduce maintenance overhead of working with data pipelines and help increase platform reliability.

● Advocate and advance modern, agile software development and help develop and foster good engineering practices.

● Help ensure the solutions are scalable, sustainable, architecturally sound, and technical debt is both incurred consciously and repaid in a reasonable time.

● Demonstrate and champion an appetite for knowledge and never stop developing as a Data Engineer.

Who you are:

● Deeply knowledgeable and passionate about modern data architecture principles, e.g., data lake, data warehouse and data mesh.

● Steady foundation in coding and are comfortable working with data in Python and SQL, and have worked with cloud technologies, e.g., AWS and Azure.

● Worked with modern data formats such as parquet, and have experience in design, develop and deploy data pipeline based on use cases, e.g., batch vs streaming.

● Extensive experience working hands-on as a Data Engineer developing large scale data solutions in an agile environment.

● Knowledgeable about data modelling, data access, and data storage techniques, and are passionate about crafting clean code and test-driving development.

● You know and care about sound engineering practices like continuous integration and delivery, defensive programming, and automated testing.

● Pragmatic and understand the trade-offs between the perfect solution and a working solution.

● Technological experience in Kubernetes, data security and privacy, distributed computing, such as Spark/Ray/Dask and microservices.