Informacje o stanowisku

Project information:

• Industry: Banking
• Rate: up to 180 pln net/h
• Contract: B2B
• Location: Gdynia/Gdańsk (1 day per week in the office)

We offer:

• Co-financing of private medical care (Medicover) and Multisport card.
• Occasional company integration meetings.
• Referral program.
• emagine mobile application – easy reporting of working time, quick access to new offers.

Description of knowledge and experience:

• 4+ years of experience as Data Engineer. 
• Experience in Spark and Python  
• Strong understanding Spark SQL or Hive SQL. 
• Experience with Hadoop/Hive ecosystem or other Big Data technologies.  
• Previous experience in creating data flows. 
• Experience with BitBucket and GIT, code versioning and branching strategy. 
• Familiarity with Agile/SAFe framework. 

Nice to have:

• Cloud Experience is a big plus (AWS, GCP, Azure). 
• Basic knowledge about machine learning models (building, validating and maintaining regression models). 
• Scala or MLOps experience. 

Project information:

• Industry: Banking
• Rate: up to 180 pln net/h
• Contract: B2B
• Location: Gdynia/Gdańsk (1 day per week in the office)

We offer:

• Co-financing of private medical care (Medicover) and Multisport card.
• Occasional company integration meetings.
• Referral program.
• emagine mobile application – easy reporting of working time, quick access to new offers.

,[Working with Spark and Python to define and maintain data ingestions and transformations., Building distributed and highly parallelized big data processing pipelines that process massive amounts of data (both structured and unstructured data) in near real-time., Leverage Spark to enrich and transform corporate data to enable searching, data visualization, and advanced analytics., Working closely with analysts and business stakeholders to develop analytics models., Collaboration with Data Scientists and Machine Learning experts., Providing detailed information about progress during PI Demo sessions. Requirements: Spark, Python, Big Data, Machine Learning, Spark SQL, SQL, Hadoop, Hive, Bitbucket, Git, SAFe, Cloud, AWS, GCP, Azure, Scala, MLOps

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