Data Engineer II: Scalable Pipelines & Risk Analytics

Mastercard Inc.; O’Fallon (MO); Hybrid; USD 92,000 - 147,000; Full time

Benefits offered by this job

Insurance (medical, prescription drug,

Dental & Vision coverage

401k with company match

Paid time off

Job summary

Mastercard seeks a Data Engineer II in O’Fallon, MO to design, build, and maintain data pipelines and products supporting credit decisioning, risk analytics, regulatory reporting, and ML initiatives.

You will collaborate with engineers, data scientists, risk analytics, and product partners to translate business needs into scalable data solutions, with a focus on data quality and reliability. This is a hybrid role with three onsite days per week.

Qualifications

• Experience designing, building, and maintaining ETL/ELT pipelines.
• Strong SQL skills and ability to optimize queries on large datasets.
• Experience with Python or similar data-processing languages.
• Experience with relational databases (Postgress) and data modeling.
• Familiarity with cloud-based data platforms and modern data engineering tech.

Responsibilities

• Design, develop, test, and maintain scalable data pipelines and datasets for ECR products.
• Build and optimize ETL/ELT workflows using SQL, Python, Databricks, and Spark.
• Develop data products supporting reporting, analytics, and credit decisioning.
• Collaborate with Product, Risk Analytics, Data Science, and Engineering teams.
• Implement data validation and quality controls to ensure data accuracy.
• Support deployment and operation of production data pipelines.
• Investigate data issues and participate in root-cause analysis.
• Contribute to cloud migration and modernization of data platforms.
• Document data solutions, pipelines, and data flows.

Skills

SQL

Python

Databricks

Apache Spark

Data modeling

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems, or related STEM

Tools

Databricks

Apache Spark

Job description

Mastercard seeks a Data Engineer II in O’Fallon, MO to design, build, and maintain data pipelines and products supporting credit decisioning, risk analytics, regulatory reporting, and ML initiatives.

You will collaborate with engineers, data scientists, risk analytics, and product partners to translate business needs into scalable data solutions, with a focus on data quality and reliability. This is a hybrid role with three onsite days per week.