Full Time Job

Sr. Data Engineer, Corporate Decision Science


New York, NY 10-14-2020
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  • Paid
  • Full Time
  • Mid (2-5 years) Experience
Job Description

The Corporate Decision Science organization at NBCUniversal drives advanced analytics by building and integrating pragmatic data science principles and products throughout the Company with focus on enabling a data-enhanced decision support and building advanced data products to inform strategy and key business decisions.
The Data Engineer will be directly responsible for developing efficient data ingestion processes and automated management; develop and operationalize of machine learning models; and building robust data platforms to enable scaling of our products.
• Process structured and unstructured data into a form suitable for analysis and reporting, empowering state-of-the-art analytics and machine learning environments for business analysts, data scientists and engineers
• Operationalize data science models and products in a cluster-computing environment working closely with data scientists to understand requirements and develop appropriate feature engineering to deliver high performing models
• Build data pipeline frameworks to automate high-volume and real-time data delivery
• Provide clear data engineering technical leadership, mentoring, and best practices for data management and quality within and across teams
• Manage multiple priorities across a mix of ad-hoc and operational projects, including managing vendors, partners and contractors as needed
• Work directly with Product Owners and customers to deliver data products in a collaborative and agile environment
• Partner with various NBCU Technology teams in the design and execution of an overall Corporate Data Syndication Strategy for Nielsen and Alternative Measurement Data
• Evangelize a very high standard of quality, reliability and performance for data models and algorithms that can be streamlined into the engineering and sciences workflow
• Grasp new technologies rapidly as needed to progress varied initiatives
• Improve automation of various processes in a distributed computing environment, recommend schema improvements, and help adjust queries and jobs orchestration

• Minimal Bachelor's Degree in Computer Science, Engineering, or other quantitative field or equivalent, Master's Degree preferred
• 4+ years' experience processing large amounts of structured and unstructured data in a cluster-computing environment or similar experience in academia
• Experience with a programming language such as Python, and the experience writing reusable and efficient code to automate analyses and data processes
• Knowledge of principles of systems at scale leveraging big data technologies like Spark, and Databricks, Airflow, Docker, and demonstrated ability to develop recommendations to architect efficient data processing systems
• Demonstrated ability to access, maintain and support application deployed in a Unix environment as well as data warehouse environments
• Hands-on knowledge of cloud-based infrastructure (AWS) is desired in at least 3 of the following AWS services: Athena, Glue, S3, Lambda, Elastic Beanstalk, ECS Fargate, EMR
• An excellent understanding of computer programming, database schema design, and engineering best practices (Dev, UAT, Prod Environment; GitHub integration etc.)
• Ability to quickly establish solutions and take advantage of ML/AI technologies
• Experience building and maintaining production-grade data pipelines
• Team-oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools

Desired Characteristics
• Experience with open source and Enterprise software, Javascript preferred
• Familiarity with relational databases and SQL and API implementations a plus
• Ability to communicate insights and findings through data visualization tools such as Tableau
• Ability to provide clear data engineering technical leadership, mentoring, and best practices for data management and quality within and across teams
• Experience with television ratings and digital measurement tools (Nielsen, Rentrak, comScore, Omniture, etc.)
• Experience and passion for the Media and Entertainment industry a plus