September 27
• Create and maintain optimal data pipeline architecture. • Identify, design, and implement internal process improvements. • Build the infrastructure required for optimal extraction, transformation, and loading of data from various sources. • Create data tools for data quality team members to enhance workflows. • Build processes supporting data transformation, data structures, metadata, and workload management.
• 8+ years of experience in Data Engineering or Software Engineering roles. • Graduate degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field. • Advanced working SQL Server knowledge and experience with relational databases and query authoring (SQL). • Familiarity with a variety of databases, NoSQL, Big Data, and Custom formats. • Experience with Visual Studio, ASP.NET Frameworks, .NET Core, and C#. • SQL Server and NoSQL experience, Java, and Internet Information Services (IIS) • Experience with multi-threading in C# and data integrity in SQL Server. • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. • Strong analytic skills related to unstructured datasets. • Experience supporting and working with cross-functional teams in a dynamic environment.
• Health care coverage designed for the mind and body. • Generous time off helps keep you energized for your time on. • Access a wealth of resources to grow your career and learn valuable new skills. • Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. • 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. • From retail discounts to referral incentive awards—small perks can make a big difference.
Apply NowSeptember 26
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Join a team of engineers to address platform needs for large organizations.