Collaborate with data scientists to ensure data is accurately extracted, transformed, and loaded for analysis and decision-making
Effectively collaborate and partner with various Scores stakeholders to deliver data driven solutions that support strategic Scores initiatives
Analyze, interpret, and manipulate large data sets to support analytic research and model development efforts
Deliver high level results supporting business-critical projects within expected timelines
Use internal technologies in the development, maintenance and improvement of tools and processes to help solve challenging business problems in predictive analytics
Support the existing code base and the overall analytic SDLC
Demonstrate self-initiative and innovation by writing new code to continuously evaluate and improve existing code base
Apply advanced data transformation techniques to optimize the processing of large datasets
Work closely with the data scientists and other data engineers in constructing the best methodologies in generating new tools, code and datasets based on project requirements

BS degree in Computer Science, Engineering, Information Technology, Management Information Systems (or equivalent work experience)
Prior/current experience working with U.S. Credit Bureau data (Preferred)
Proven programming skills in Python (Highly Preferred), Java/Groovy, Perl and/or Shell scripting
Demonstrated expertise utilizing Linux (RedHat) and Windows operating systems
Expertise in AWS services- SageMaker, Jupyter Notebooks, S3, Athena
Proven expertise analyzing large datasets and applying data-cleaning techniques along with strong data wrangling skills
Experience working with big data technology (Spark, Hadoop, etc.)
Familiarity with relational databases (Oracle, mySQL, etc)
Familiarity with Eclipse IDE
Familiar with version control tools like GitHub or Bitbucket

Lead Data Engineer, Python, Java, AWS

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