Big Data Engineer

We are looking for a Big Data Engineer
to join our R&D team

Description

We are looking for an outstanding Data Engineer who is proficient in Big Data Systems to support Machine Learning / Economics based Statistical Models, Algorithms, and Solutions at scale.

As a Big Data Engineer at MorphL you will work closely with Scientists, Economists and Engineers to architect & implement solutions that handle large volumes of data, author complex data pipelines, and create automated reporting. You will drive actions that scale across enterprises while working on complex AI problems.

This is a unique, high visibility opportunity for someone to have a large impact, dive deep into large-scale enterprise problems and, enable measurable actions on large scale digital products & services.

If you are a sharp, experienced engineer with demonstrated capabilities in implementing machine learning and analytical solutions on Big Data stacks we want to hear from you.

Other details

Mid-Senior level

Bucharest based

Great startup culture

Qualifications

  • Bachelor's degree in Computer Science, Engineering, Technical Science or 3 years of IT/Programming experience.
  • Minimum 2+ years of expertise in designing, implementing large scale data pipelines for data curation and analysis, operating in production environments, using Spark, pySpark, SparkSQL, with Java, Scala or Python on premise or on Cloud (AWS, Google or Azure)
  • Minimum 1 year of designing and building performant data models at scale for using Hadoop, NoSQL, Graph or Cloud native data stores and services.
  • Minimum 1 year of designing and building secured Big Data ETL pipelines, for data curation and analysis of large scale production deployed solutions.

Tech Stack

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Jobs at MorphL

We're excited to hear from you and you should know that our application process is a bit different - you'll need to make an inference about the correct e-mail address to send your resume/CV.



This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 779790.