S&P Global Ratings
Financial Services
BigDataEngineerLead
“Big Data Engineer Lead at S&P Global Ratings. Skills: Big Data, AWS, Data Engineering, Data Pipelines. Design and develop data pipelines. Work closely with Data Science team”
What You'll Achieve.
Empowers analysts to determine insights into revenue; Power products across the organization; Build a data eco system that supports AI products at scale
Industry & Context.
Analytical thinking
What They're Looking For.
Must Have
BS or MS degree in Computer Science or Information Technology, 8+ years of experience as data engineer, 4+ years of hands-on experience in implementing data lake systems using AWS cloud technologies, 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), Programming languages including Python, Scala, Java, or similar, Expert knowledge of Agile approaches to software development
Nice to Have
Experience with machine learning libraries and frameworks (such as TensorFlow, PyTorch, Scikit-learn, or MLlib), Exposure to R, SparklyR, and other R packages, Monitors industry trends and develops and presents substantive technical recommendations to senior management, Financial services industry experience, Excellent analytical thinking, interpersonal, oral and written communication skills with ability to influence both IT and business partners, Ability to prioritize and manage work to critical project timelines in a fast-paced environment
What You'll Do.
Design and develop data pipelines
Work closely with Data Science team
Provide technical expertise in AWS cloud technologies
Build and maintain data environment
Support analytics by building data lake
Work with machine learning engineering team
Ensure data governance principles adopted
Partner with chief data office
Evaluate new technologies
Ensure compliance through adoption of standards
How You'll Work.
Team & Collaboration
Work closely with Data Science team; Partner with chief data office; Partner with enterprise architecture organization; Collaborate with each other and customers
Communication Scope
Oral and written communication skills; Ability to influence both IT and business partners
Process & Methodology
Manage work to critical project timelines
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