Data Engineering Analyst II

at  EXPERIAN

ABOUT US, BUT WE’LL BE BRIEF

Experian is the world’s leading global information services company, unlocking the power of data to create more opportunities for consumers, businesses, and society. We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to work for. In addition, for the last five years we’ve been named in the 100 “World’s Most Innovative Companies” by Forbes Magazine. Experian prioritizes our culture and look to bring people to the team who are passionate about their jobs, who are easy to work with, and who continue to value team over self.
We have 23,000 people operating across 44 countries and every day we’re investing in new technologies, talented people, and innovation to help all our clients maximize every opportunity.

JOB DESCRIPTION

Data Engineering – Growing the analytic environment:

• Conversion of current ETL processes to automated versions
• Creation of new database tables and related development of ETL processes to keep tables updated on a regular schedule
• Processing ETLs, monitoring the environment to ensure successful data processing and correcting any data quality issues
• Integration of new applications and tools to further increase the overall level of quality and automation in the ETL processes
• Updating and modifying the Redshift environment to reflect changes in data, user requirements, and the growing needs of the business
• Maintaining data dictionary and database documentation and reference materials

Credit, risk & marketing modeling:

• Conduct annual model validations on credit, risk and marketing models
• Produce annual performance charts and score distribution graphics for Clarity models
• Research model stability by analyzing shifts in scores and attributes over time

Product development:

• Develop and maintain a product designed to track changes in attribute and model distributions on a quarterly basis.
• Support the development of product proofs-of-concept and other initiatives by creating structured data sets, performing quality control and peer reviews, and assisting senior team members in conducting analytics.

QUALIFICATIONS

• Bachelor’s degree in computer science, data science, data engineering or similar field of study
• 2-5 years experience in data engineering, building and maintaining database tables and developing ETL processes and QA procedures with expertise in cloud computing and data warehousing
• Mastery of SQL, Python and PySpark
• Functional knowledge of Github and versioning control
• Knowledge of AWS products, specifically: Redshift, S3 storage, EMR, EC2
• Experience with database management & automated reporting
• Strong analytical and problem-solving skill

Preferred:

• Advanced degree in computer science, data science, data engineering or similar field of study
• Knowledge of financial services, consumer lending, risk management, credit bureau data, credit scores
• Experience with R Studio
• Experience with other AWS applications such as Lambda or EventBridge
• Proficiency with Tableau
• Functional proficiency in applied statistical analysis

Please refer the Job description for details