Big Data Engineer

Last updated 13 days ago
Location:Macquarie Park
Job Type:Full Time

The Data Platform Management team has been being established in the Group IT team at Optus to help realise the vision of becoming a customer-centric organisation, driven by a data and analytics capability that enhances customer interactions and revenue generation.

The Big Data Engineer is responsible for development and automation of Big Data ingestion, transformation and consumption services; adopting new technology; and ensuring modern operations in order to deliver consumer driven Big Data solutions.


The role

  • Implement request for ingestion, creation, and preparation of data sources
  • Develop and execute jobs to import data periodically/ (near) real-time from an external source
  • Setup a streaming data source to ingest data into the platform
  • Delivers data sourcing approach and data sets for analysis, with activities including data staging, ETL, data quality, and archiving
  • Design a solution architecture to meet business, technical and user requirements
  • Profile source data and validate fit-for-purpose
  • Works with Delivery lead and Solution Architect to agree pragmatic means of data provision to support use cases
  • Understands and documents end user usage models and requirements

The perks

We offer all kinds of benefits, such as:

  • Onsite facilities at Macquarie Park such as a Gym, GP, Mini-Mart, Cafes
  • Training, Mentoring and further learning opportunities
  • Staff busses to Epping and Wynyard, and back again

About you

Preferred skills and experience include:

  • Bachelor’s degree in maths, statistics computer science, information management, finance or economics
  • 8+ years’ experience working in Data Engineering and Warehousing.
  • 3 -5 years’ experience integrating data into analytical platforms
  • Experience in ingestion technologies (e.g. Sqoop, NiFi, flume), processing technologies (Spark/Scala) and storage (e.g. HDFS, HBase, Hive)
  • Experience in data profiling, source-target mappings, ETL development, SQL optimisation, testing and implementation
  • Expertise in streaming frameworks (Kafka/Spark Streaming/Storm) essential
  • Experience in building Microservices, Rest APIs, Data as a Service architectures.
  • Experience managing structured and unstructured data types
  • Experience in requirements engineering, solution architecture, design, and development / deployment
  • Experience in creating big data or analytics IT solution
  • Track record of implementing databases and data access middleware and high-volume batch and (near) real-time processing

You would be a self-starter with the ability to work independently and multitask several different activities across critical deadlines in a high-pressure environment.