Big Data Engineer (S&P Global Ratings)
- New York, NY, USA
- Permanent, Full time
- S&P Global
- 18 Apr 19
Big Data Engineer (S&P Global Ratings)
S&P Global Ratings is looking for an experienced Big Data Engineer to join Data Engineering team within Chief Data Office, a team of data and technology professionals who define and execute the strategic data roadmap for S&P Global Ratings. The successful candidate will participate in the design and build of S&P Ratings cloud based analytics platform to help develop and deploy advanced analytics/machine learning solutions.
You will be an expert contributor and part of the Rating Organization's Data Services Team. This team, who has a broad and expert knowledge on Ratings organization's critical data domains, technology stacks and architectural patterns, fosters knowledge sharing and collaboration that results in a unified strategy. All Data Services team members provide leadership, innovation, timely delivery, and the ability to articulate business value. Be a part of a unique opportunity to build and evolve S&P Ratings next gen analytics platform.
Our Hiring Manager Says
If you are an individual that brings demonstrated experience of delivering big data projects as a data engineer, this is an excellent opportunity. I am looking for someone with sound technical knowledge, can be hands-on, worked on transformational initiatives, and can drive results.
- Design and develop efficient and scalable data pipelines between enterprise systems and analytics platform
- Work closely with Data Science team and participate in development of feature engineering pipelines
- Provide technical expertise in the areas of design and implementation of Ratings Integrated Data Facility with modern AWS cloud technologies such as S3, Redshift, EMR, Hive, Presto and Spark
- Build and maintain a data environment for speed, accuracy, consistency and 'up' time
- Support analytics by building a world-class data lake environment that empowers analysts to determine insights into revenue and power products across the organization
- Work with the machine learning engineering team to build a data eco system that supports AI products at scale
- Ensure data governance principles adopted, data quality checks and data lineage implemented in each hop of the data
- Partner with the chief data office, enterprise architecture organization to ensure best use of standards for the key data domains and use cases
- Be in tune with emerging trends Big data and cloud technologies and participate in evaluation of new technologies
- Ensure compliance through the adoption of enterprise standards and promotion of best practice / guiding principles aligned with organization standards
Experience & Qualifications:
- BS or MS degree in Computer Science or Information Technology
- 5+ years of experience as data engineer at an innovative organization
- 3+ years of hands-on experience in implementing data lake systems using AWS cloud technologies such as S3, Redshift, EMR, Hive, Presto and Spark
- Expert managing AWS services (EC2, S3, Route 53, ELB, VPC, cloudwatch, Lambda) in a multi account production environment
- Experience With Machine Learning Libraries and Frameworks (TensorFlow , MLlib) is an added advantage
- Exposure to R , SparklyR , and Other R packages is a Plus
- Experience with development frameworks as well as data and integration technologies such as Informatica, Python, Scala
- Expert knowledge of Agile approaches to software development and able to put key Agile principles into practice to deliver solutions incrementally.
- Monitors industry trends and directions; develops and presents substantive technical recommendations to senior management
- Excellent analytical thinking, interpersonal, oral and written communication skills with strong ability to influence both IT and business partners
- Ability to prioritize and manage work to critical project timelines in a fast-paced environment
- Financial services industry experience