Big Data ETL Developer. ( Hadoop )

10 июля 2019    26

Bachelor degree in Computer Science, Information Systems or equivalent quantitative field and 5+ years of experience in a similar ETL role
Experience working with and extracting value from large, disconnected and/or unstructured datasets
Demonstrated ability to build processes that support data transformation, data structures, metadata, dependency and workload management
Strong interpersonal skills and ability to project manage and work with cross-functional teams
Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases, especially SQL Server and Hive
Experience building and optimizing ‘big data’ data pipelines, architectures and data sets
Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement

Experience required with the following tools and technologies:

Major Hadoop ecosystem distributions such as HDP, Cloudera etc. HDP is preferred
Public cloud such as Azure, AWS etc. Azure is preferred
JSON document processing
Apache Hive and HBase, Microsoft SQL Server
Apache NiFi, Kafka
Object-oriented/object function scripting languages such as Python, Java etc.

Competitive salary (discussed with a successful candidate)
Opportunities for professional and career growth
Flexible working schedule
Friendly dynamic international Agile team
Fruits, snacks and fully equipped kitchens in the office
Recreational zones, play-rooms
Voluntary health insurance for employees including dental services
Training programs, including English classes
Opportunity to travel to professional conferences, external courses, and seminars

Work closely with system architects and data engineer to create and optimise the architecture of ETL system
Design and build the ETL tools to extract, transform, aggregate and store the data
Always angle for greater efficiency and robustness of the ETL process to support big volume of data flow among different data systems.

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