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 customerequirements.
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
Responsibilities - 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 Nasdaqig 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)
- ductionalizee analytical processes developed by the Data Science team
- Productionalize erb) 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 Nasdaqata Platform
Background 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.
Experience 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.
Education - Bacheloregree from top tier university in Computer Science, Engineering, Physics, Mathematics, or similar quantitative discipline.
- Masteregree a plus.
Skills Required - 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
Preferred - 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
Nasdaq is an equal opportunity employer. We positively encourage applications from suitably qualified and eligible candidates regardless of age, color, disability, national origin, ancestry, race, religion, gender, sexual orientation, gender identity and/or expression, veteran status, genetic information or any other status protected by applicable law.
