Big Data Engineer

Big Data Engineer

  • Location


  • Sector:

    Data Scientist

  • Job Type:


  • Contact:

    Gina Maucieri

  • Job Reference:


  • Published:

    over 1 year ago

  • Expiry date:


  • Start Date:


  • :


Big Data Engineer

The ideal candidate has experience in building and optimizing big data systems. He will work closely with our data scientists and analysts to help direct the flow of data within the pipeline and ensure consistency of data delivery and utilization across multiple projects.


  • Work closely with other data and analytics team members to optimize the company’s data systems and pipeline architecture
  • Design and build the infrastructure for data extraction, preparation, and loading of data from a variety of sources using technology such as SQL and AWS
  • Build data and analytics tools that will offer deeper insight into the pipeline, allowing for critical discoveries surrounding key performance indicators and customer activity
  • Always angle for greater efficiency across all of our company data systems.



  • Graduate degree in Computer Science, Information Systems or equivalent quantitative field and 5+ years of experience in a similar Data Engineer role.
  • 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 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.
  • Experience with the following tools and technologies:
  • Hadoop, Spark, Kafka,
  • Relational SQL and NoSQL databases
  • Data pipeline/workflow management tools such as AWS Glue
  • AWS cloud services such as S3, EMR, RDS and Redshift
  • Stream-processing systems such as AWS Kinesis
  • Scripting languages such as Python