Data Engineer

As an analytics company we are tasked with the role of making sense of the data that belongs to our client. A Data Engineer would need to work closely with our core team in architecting solutions that ensures the storage and retrieval of data, basis our varied client needs.

The Person

High Energy and passion to learn
High sense of ownership
Ability to work in a fast-paced and deadline driven environment
Loves technology
Problem solver

The Ask

Skills to work in a challenging, complex project environment
  • Naturally curious and passionate about consumer behaviour.
  • A high level of motivation, passion and high sense of ownership.
  • Excellent communication skills needed to manage an incredibly diverse slate of work, clients and team personalities.
  • Flexibility to work on multiple projects and deadline-driven, fast-paced environment.
  • Ability to work in ambiguity and manage chaos basis our varied client needs.
  • A successful history of manipulating, processing and extracting value from large disconnected datasets.
  • Working knowledge of message queuing, stream and batch processing.
  • Strong project management and organizational skills.
  • Experience supporting and working with cross-functional teams in a dynamic environment.
  • We are looking for a candidate with years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. Experience of the following software/tools would be needed:
    • Big data tools: Hadoop, Spark, Kafka, etc.
    • Relational SQL and NoSQL databases, including Postgres and Cassandra.
    • Any AWS cloud services: EC2, S3, Athena, Lambda, EMR, RDS, Redshift, Dynamo DB etc.
    • Any processing systems: Storm, Spark-Streaming, etc.
    • Any object-oriented/object function scripting languages: Python, Scala, Java etc.
    • Containerized applications like Dockers and Kubernetes: will be a plus.
Project Delivery skills
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design and implement internal process improvements: automating manual processes, optimizing data delivery,
re-designing infrastructure for greater scalability etc.
Build the infrastructure required for optimal extraction, transformation and loading of data from a wide variety of data sources.
Work with stakeholders including the Executive, Product, Data and/or Design teams to assist with data-related technical issues and support their data infrastructure needs.
Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
Create data tools for analytics and data science team members to assist them in building and optimizing our product into an innovative industry leader.

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