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Big Data Engineer - AWS

  • Location: Sydney, 2000
  • Salary: Negotiable per day
  • Job Type:Permanent

Posted 19 days ago

About our Client:

I am currently working with an international financial services organization who are undertaking a large digital transformation. A key stream of work is the overhaul of their data environment building a new data lake to support a number of key business driven projects.

The Opportunity:

Hands on Big Data Engineer will be responsible for data pipeline architecture and Data Analysis working on AWS platform.

About you:

  • You will expand and optimise our clients' data and data pipeline architecture, as well as optimise their data flow and collection for cross functional teams.
  • 2 years of experience working with AWS webservices (S3, EC2 and Redshift)
  • Hands on experience working with ETL, Hadoop, Spark, Scala, Strong Scala, Python and SQL knowledge
  • Experience with data streaming using technologies like Kafka, Kinesis, etc. and data frameworks like Apache Beam, Flink, Spark etc.
  • Should have good stakeholder management and communications skills will allow you to successfully keep the team updated on deliverables and ensure key project stakeholders are aware of progress against project milestones.
  • Provide thought leadership in support of design and implementation of a big-data platform. Lead in the transformation from structured to unstructured data, evaluating new technologies and approaches leading to scalable Big Data platforms.


The Successful candidate

With both permanent and contract positions available we encourage candidates with skills in the above area to contact the team at Hydrogen for confidential discussions. We are seeking intellectually capable, personable and change driven individuals who want to be part of a market leading consulting organisation. First class communication skills in both the written and verbal form will be required.

What's on offer?

The opportunity to work with world class thought leaders in the digital transformation, Big data, Data science, RPA and AI space. International and local career progression.

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