Salary: 13.000 - 16.000 RON net per month
Requirements:- Skills
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- Expertise in the implementation of end-to-end data processing chains
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- Mastery of distributed development
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- Basic knowledge and interest in the development of ML algorithms
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- Knowledge of ingestion frameworks
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- Knowledge of Beam and its different execution modes on DataFlow
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- Knowledge of Spark and its different modules
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- Experience with Java
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- Experience with Python
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- Knowledge of the GCP ecosystem DataProc, DataFlow, BigQuery, Pub-Sub, PostgreSQL/Composer, Cloud Functions, StackDriver)
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- Knowledge of the use of Solace
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- Knowledge of Spotfire & Dynatrace
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- Knowledge of the ecosystem of NOSQL databases
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- Knowledge in building data product APIs
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- Knowledge of Dataviz tools and libraries
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- Ease in debugging Beam (+ Spark) and distributed systems
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- Popularization of complex systems
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- Control of the use of data notebooks
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- Expertise in data testing strategies
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- Strong problem-solving skills, intelligence, initiative and ability to resist pressure
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- Excellent interpersonal skills and great communication skills (ability to go into detail)
- General role:
- Contribute to the business value of Data-oriented products based on on-premise Datalake or on cloud environments, by implementing end-to-end data processing chains, from ingestion to API exposure and data visualization
- General responsibility: Quality of data transformed in the Datalake, proper functioning of data processing chains and optimization of the use of resources of on-premise or cloud clusters by data processing chains
- General skills: Experience in the implementation of end-to-end data processing chains and Big data architectures in the Cloud (GCP) mastery of languages and frameworks for the processing of massive data in particular in Streaming Mode (Beam DataFlow , Java, Spark / Scala / DataProc). Practice agile methods.
- Role
- You will set up end-to-end data processing chains in cloud environments and in a devops culture, You will work on brand new products, for a wide variety of functional areas (Engineering, Connected vehicle, Manufacturing, IoT, Commerce, Quality, Finance), with a solid team to support you.
- Main responsibilities
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- During the definition of the project
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- Design of data ingestion chains
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- Design of data preparation chains
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- Design of basic ML algorithms
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- Data product design
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- Design of NOSQL data models
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- Data visualization design
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- Participation in the selection of services / solutions to be used according to usage
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- Participation in the development of a data toolbox
- During the iterative realization phase
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- Implementation of data ingestion chains
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- Implementation of data preparation chains
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- Implementation of basic ML algorithms
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- Implementation of data visualizations
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- Use of ML framework
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- Implementation of data products
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- Exhibition of data products
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- Configuration of NOSQL databases
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- Distributed processing implementation
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- Use of functional languages
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- Debugging distributed processing and algorithms
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- Identification and cataloging of reusable items
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- Contribution to the evolution of work standards
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- Contribution and advice on data processing problems
- During integration and deployment
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- Participation in problem solving
- During serial life
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- Participation in the monitoring of Operations
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- Participation in problem solving
- API
- Big Data
- BigQuery
- Cloud
- Composer
- DevOps
- Dynatrace
- GCP
- IoT
- Support
- Java
- NoSQL
- PostgreSQL
- Python
- Scala
- Spark
- Data-Engineer
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last updated 20 week of 2026