North America / United States / IL / Chicago /

Technology & Engineering

#: 743999735886869 / REF1917D

Not Applicable


Job Description

Our NielsenIQ Technology teams are working on our new “Connect” platform, a unified, global, open data ecosystem powered by Microsoft Azure. Our clients around the world rely on NielsenIQ’s data and insights to innovate and grow.

As a DataOps Transformation – Data Engineer, you’ll be part of a team of smart, highly skilled technologists who are passionate about learning and prototyping cutting-edge technologies. Right now our platform is based in Java, Angular, Spring Boot, Apache NiFi, Mongo, Postgres and Snowflake, and we continue to adopt the best of breed in cloud-native, low-latency technologies. We value CI/CD in everything that we develop. Our team is co-located and agile, with central technology hubs in Chicago, Madrid and Chennai. 


  • Design data pipelines for machine learning to increase efficiency in US Data Operations
  • Piping and processing massive data-streams in distributed computing environments
  • Create harmonized data pipelines with predictive modeling algorithms
  • Drive projects that can be effectively supported by ops and tech teams
  • Create an open ecosystem for Data Operations and other Nielsen functions to more quickly access and analyze data


  • Ability to collaborate and influence with other functional areas as a team and deliver results on-time
  • Ability to present and explain methods and operational solutions to executive leadership
  • Expertise in Python/Pyspark or other Big Data architecture (Hive/Hadoop)
  • Deep understanding of Data Engineering and Warehousing techniques with SQL
  • Experience building/accessing API’s with a python framework using CI/CD framework
  • Excellent English communication skills, with the ability to effectively interface across cross-functional technology teams and the business 
  • 1-2 years of experience in quantitative analysis, and a strong educational background in an engineering or technical field
  • Minimum B.S. degree in Computer Science, Computer Engineering or related field