Big Data Engineer Lead

S&P Global • New York, NY

1d

About The Position

About the Role: Grade Level (for internal use): 12 The Team: 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. Responsibilities and Impact: 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, and distributed computing frameworks 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 in 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

Requirements

• BS or MS degree in Computer Science or Information Technology
• 8+ years of experience as data engineer at an innovative organization
• 4+ years of hands-on experience in implementing data lake systems using AWS cloud technologies such as S3, Redshift, EMR, and distributed computing frameworks (such as Spark, Hadoop, or Flink)
• Expert managing AWS services (EC2, S3, Route 53, ELB, VPC, CloudWatch, Lambda) in a multi-account production environment
• Experience with development frameworks and data integration technologies (such as Informatica, Talend, or Apache NiFi) and programming languages including Python, Scala, Java, or similar
• Expert knowledge of Agile approaches to software development and able to put key Agile principles into practice to deliver solutions incrementally

Nice To Haves

• Experience with machine learning libraries and frameworks (such as TensorFlow, PyTorch, Scikit-learn, or MLlib) is an added advantage
• Exposure to R, SparklyR, and other R packages is a plus
• Monitors industry trends and directions; develops and presents substantive technical recommendations to senior management
• Financial services industry experience
• 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

Responsibilities

• 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, and distributed computing frameworks
• 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 in 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

Benefits

• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible Downtime: Generous time off helps keep you energized for your time on.
• Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
• Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
• Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
• Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level