24 days old

Data Engineer Specialist

Boston, MA 02210
  • Job Code
  • Payrate
    $115,000 To $120,000

Please carefully review the position requirements before submitting a potential candidate for consideration.

Nasdaq is seeking highly motivated Senior Data Engineer Specialist to join a small, highly collaborative team and help create the next generation of data products for trading and investing.

Primarily responsible for taking the defined business requirements and provides analytical, modelling, dimensional modeling and testing to provide best outcomes for design against these customer's requirements.

Analysis concentrates on understanding the business needs for data and information. The data engineer translates business information needs into data structures that are adaptable, extensible and sustainable


  • Develop production-grade data pipelines and ETL processes to support leading-edge analytics and big data processing
  • Curate massive amounts of data and make it accessible via state-of-the-art technologies
  • Review internal and external technological techniques, processes, and tools - to improve efficiency and better serve Nasdaq clients worldwide ?
  • Gather new product requirements from business stakeholders

    • Design new production workflows and architectures to support those products

  • Collaborate with Data Scientists and Software Developers to develop experiments and deploy solutions to production
  • Rapidly integrate new content sets (financial and non-financial) into Nasdaq's big data ecosystem
  • Contribute ideas and constructive feedback to the tech and business teams
  • Stay current on technological trends
  • Take ownership of new projects and initiatives
  • Stay current on technological and analytical trends
  • Be passionate about data and big data tech
  • Maintain positive attitude
  • Motivate and coach other members of the team

Example Projects

  • Develop data ingestion and normalization framework that can collect and process data from hundreds of sources daily (and in real-time)
  • "Productionalize" the analytical processes developed by the Data Science team

    • Productionalize - (verb) Performance tune models, automate data processing workflow, deploy in a highly-available and scalable way

  • Develop analytical libraries and tools that allow the Data Science team to take full advantage of Nasdaq's Data Platform


We will consider candidates from a wide range of backgrounds, however, the many of the problems the candidate would be tasked with solving will require writing complex programs, designing systems, and analyzing data. Therefore, candidates with a computer science or engineering background are preferred.


Successful candidates will have:

  • Minimum 5 years of professional experience in engineering or other technical role
  • Experience deploying applications in a production or mission-critical environment
  • Experience in financial services is a plus.


  • Bachelor's Degree from top tier university in Computer Science, Engineering, Physics, Mathematics, or similar quantitative discipline.
  • Master's Degree a plus.



  • Knowledge of cloud platforms and common architectures: AWS, Google
  • Strong Familiarity with Big Data technologies and architectures: Hadoop, Spark, Kafka, etc.
  • Good Programming Skills: Python, Java, Scala, R, SQL
  • Experience with containers and scalable computing platforms: Docker (ECS), Mesos, Kubernetes
  • Good verbal and written communication


  • Familiarity with Apache Spark: tuning and maintaining clusters, optimizing jobs, etc.
  • Familiarity with analytical techniques and machine learning workflows
  • Familiarity with financial data sets and use cases
  • Strong familiarity with AWS
  • Knowledge of Lambda architectures
  • Excellent communication skills


  • Information Technology

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