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Are you ready to “Build the Future” with us?

We were established in 2012 to enlighten our customers’ path with the excitement of creating value in the technology world.

As we continue our way as an R&D center since 2017, we continue to be one of the new companies that value people, pursue new technologies with passion, and break grounds in the IT sector with our agile and reliable working culture, and we are looking for a “Senior Big Data Engineer” for our Big Data & DWH Team.

Desired Skills and Experience

• BS degree or higher in a technology related field (Computer Engineering, Computer Science, Math, Information Systems, Industrial Engineering or another quantitative field)
• 5 + years of experience in Big Data Engineering role
• Nice to have building a big data platform (Hadoop, Cloudera, GCP), install and maintain the open source applications (Hdfs, airflow, spark, nifi, kafka)
• Experience with Hadoop components such as HDFS, Hive, Spark, Kafka, Flink, Hive, Apache Airflow, Nifi etc.
• Experience in designing, building and managing custom applications to process large amounts of data in a Hadoop ecosystem
• Deep knowledge of Python / PySpark and nice to have one programming language such as Scala, Java
• Expert level experience in real-time stream (Beam,Spark Streaming) or batch processing (Spark, hive, python) with scale in mind
• Proficiency in data manipulation using e.g. SQL, NOSql, Spark, pandas or similar
• Preferably, experience with at least one BI tool (Looker, PowerBI, Qlik Sense, Grafana)
• Preferably, good understanding of data modeling, data processing, ETL and data lake concepts. (Plsql, ODI, Pentaho)
• Strong problem solving, data analysis, interpretation, data visualization skills and ability to communicate data insight
• Have a good command of written and spoken English

Responsibilities

• Designing and building big data platforms and installing the big data tools
• Developing, testing, deploying and maintaining batch and streaming data pipelines
• Monitoring big data platforms with automation and maintaining if necessary
• Analyzing business requirements for project development
• Designing and scaling data ingestion systems with high availability and reliability