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BigData Engineer with Cloud:Data Lake Architect;Sys Integ; Automation

Posted on Jun 14, 2019 by McCabe & Barton

Zürich, Switzerland
Information Technology
3 Feb 0001
Annual Salary

Big Data Engineer with Cloud: Data Lake Architectures;Sys Integ; Automation Pipelines Zurich 130/150k CHF


Bachelor's degree in computer science, computer engineering, management information systems, related discipline or equivalent experience

5 Years of Experience in Big Data Platform and Data Lake Architectures

At least 5 Years of Experience in planning, realization and operation of Big Data Platforms

At least 5 Years of Experience in System Integration

A least 5 Years of Experience building automation pipelines, CI/CD using Ansible for Platforms

3-5 Years of Experience in Hortonworks HDP, Cloudera CDH

Experienced in implementing complex security requirements in the financial industry

good abstraction and conceptual skills combined with a self-reliant, team-minded, communicative, proactive personality


You'll be working in close association the Advanced Analytics (Big Data Analytics) team in Zurich. We offer you a highly motivated and experienced team with in-depth knowledge about Advanced Analytics, building models and algorithms. You'll operate and maintain the whole platform end to end and work closely with the development teams. This role include significant responsibilities and development possibilities.


engineer and integrate the platform from a technology point of view

engineer core Big Data platform capabilities


a passionate Big Data Engineer looking for new challenges

proactive, looking for creative and innovative solutions

a flexible, open-minded and cooperative person

interested in working in a fast-paced international environment as part of an international team

Experience with IBM Power Systems is of advantage

Experience with IBM Watson Studio Local and the integration with IBM DB2, IBM Big SQL, HDFS, Ranger, Hive, Yarn is of advantage

Experience with IBM DB2 is a plus

Expert understanding of ETL principles and how to apply them within Hadoop is a plus

Reference: 720946619