Big Data Engineer: 2 x hires within a new Data Science Practice

Summary about this job

Detail information about job Big Data Engineer: 2 x hires within a new Data Science Practice. Terms and conditions vacancy

We are currently recruiting two x Big Data Engineers for an exciting new data science team, within a large enterprise in Melbourne CBD. This will be a cutting-edge data science and engineering practice, that delivers commercially valuable projects to address a range of business needs and stakeholders. Some of the different features of this role compared to other positions include;

• Working closely with a very high calibre of data scientists as colleagues (in small squads)
• Varied big data and machine learning environments: not limited to; Apache Spark, Hadoop, Linux/UNIX, Python, Scala, Hive, SQL, R & more
• This is a data engineering role where you will work in lean agile squads to deliver commercial analytics projects – often leveraging cutting edge machine learning
• Varied use cases – e.g. using ML to optimise marketing personalisation, optimise logistics, build pricing models, use data science to improve finance or HR department outcomes, etc.
• Start-up culture, with a focus on getting working solutions into production and building out MVPs, not long, drawn out POCs that get shelved
• The focus is not on data migration or rebuilding a traditional Teradata Datawarehouse in Hadoop..!

Given the large technical challenges with a production big data and data science stack, we are seeking experienced applicants with significant local Australian experience in production big data teams, cloud / software / IT Vendors, or similar.

Mandatory Skills/Experience:

• You must have outstanding communication skills, ideally with some experience consulting/presenting/dealing with senior level stakeholders.
• Experience with: a modern big data stack (such as Apache Spark + Hadoop / Flink / Amazon EMR / MapR Converged Data Platform/Microsoft Azure Spark) 
• Linux or UNIX platform experience – including strong abilities with Python or Shell scripting
• Must have worked closely with data scientists / analytics teams before. 

 Desirable Skills/Experience:

• Cloud experience is highly advantageous – there will be On-prem, Azure and AWS big data deployments in this role (depending on use-case and data environment/constraints)
• Excellent soft skills and a desire to use & improve business acumen. You should be comfortable explaining to non-engineering stakeholders things such as; cost-benefit of different solutions,
• Ability to help data scientists with building robust solutions and writing better quality production code and tests!
• Comfortable dealing with senior stakeholders, presenting ideas and running meetings and scoping discussions
• Familiarity with data science and machine learning concepts – and an interest in learning more!

Please note: preference will be given to applicants already located and living in Melbourne. We will consider applicants if they have Australian citizenship or Permanent Resident visa status and can relocate at short notice.  

We will discuss benefits and more details with all short-listed candidates. A very brief summary would be:

• Flat-structured team, but with great resources, problems, internal customers and data at a proper ‘big data’ scale
• Accomplished and extremely talented peers on the data science side – with a view for strong collaboration, not common in most companies
• Huge potential for learning further from peers (e.g. cloud / big data / productionised machine learning and data science applications)
• Modern tech and data science stacks