Create and maintain an optimal data pipeline architecture

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 using SQL and AWS big data technologies

Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics

Work with stakeholders including the Executive, Product, Data and 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 scientist team members that assist them in building and optimizing our product into an innovative industry leader

Work with data and analytics experts to strive for greater functionality in our data systems

Minimum 3 years of experience in a Data Engineer role

A graduate degree in Computer Science/Statistics/Informatics/Information Systems or any other quantitative field

Strong analytical skills related to working with unstructured datasets

Worked with big data tools like Hadoop, Scala, Spark or Kafka

Experience with AWS cloud services like EC2, EMR, RDS and Redshift

Experience with stream processing systems like Storm and Spark Streaming etc

Experience with object-oriented/object function scripting languages: Java, Scala, python, etc