Lead Data Engineer

3 days ago


O Fallon, United States Mastercard Full time
About the Role

We are seeking a highly skilled Lead Data Engineer to join our Security Solutions Data Science team at Mastercard. As a key member of our team, you will be responsible for designing and developing data pipelines to automate repetitive tasks within data science and data engineering.

Key Responsibilities
  • Collaborate with data scientists to understand the existing modeling pipeline and identify optimization opportunities.
  • Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling.
  • Design and develop data pipelines to automate repetitive tasks within data science and data engineering.
  • Partner with software engineering teams to deploy and validate production artifacts.
  • Identify patterns and innovative solutions in existing spaces, consistently seeking opportunities to simplify, automate tasks, and build reusable components for multiple use cases and teams.
  • Create data products that are well-modeled, thoroughly documented, and easy to understand and maintain.
Requirements
  • Good knowledge of Linux / Bash environment.
  • Experience in the following platforms: Python, Pyspark, Airflow, CI/CD, JIRA, Hadoop, SQL, Databricks.
  • Good communication skills.
  • Highly skilled problem solver.
  • Exhibits a high degree of initiative.
  • At least an undergraduate degree in CS, or a STEM related field.
Preferred Qualifications
  • Graduate degree in CS, Data Science, Machine Learning, AI or a related STEM field.
  • Data Engineering Experience.
  • Experience with Java.
  • Experience with Jenkins.
  • Experience in with data engineering on petabyte scale data.
  • Understands and implements methods to evaluate own work and others for error.
About Mastercard

Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.


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