M

Mastercard

Processes payments across a global network

Data Engineer 2

Data EngineeringConfirmed live in the last 24 hours
Full-timeO'Fallon, MO, USA

About the Job

Requirements

  • Experience as a Data Engineer or in a similar technical role, with a solid understanding of core data engineering concepts, methodologies, and best practices.
  • Experience designing, building, and maintaining ETL/ELT pipelines and data transformations.
  • Strong SQL skills, including the ability to write and optimize queries to retrieve, transform, and analyze large datasets efficiently.
  • Experience with Python or another programming language used for data processing and automation.
  • Experience working with relational databases, including PostgreSQL, and an understanding of data modeling and database design.
  • Familiarity with cloud-based data platforms and modern data engineering technologies.
  • Familiarity with distributed data processing technologies such as Databricks, Apache Spark, or comparable platforms.
  • Understanding of data testing, validation, and quality practices to ensure accuracy and consistency across data pipelines.
  • Ability to troubleshoot complex data issues and develop effective solutions.
  • Ability to manage multiple tasks and priorities while working effectively in a fast-paced environment.
  • Ability to work independently while collaborating effectively across cross-functional and Agile teams.
  • Ability to communicate technical concepts clearly to technical and non-technical stakeholders verbally and in writing.
  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline; equivalent practical experience will also be considered.

Responsibilities

  • Design, develop, test, and maintain scalable data pipelines, transformations, and datasets supporting ECR products and initiatives.
  • Build and optimize ETL/ELT workflows using SQL, Python, Databricks, and Spark.
  • Develop and maintain curated data products that support reporting, analytics, credit decisioning, and other business use cases.
  • Partner with Product, Risk Analytics, Data Science, and Engineering teams to understand requirements and translate them into effective technical solutions.
  • Implement data validation, testing, and quality controls to ensure data accuracy, consistency, and reliability.
  • Support the deployment, monitoring, and ongoing operation of production data pipelines and workflows.
  • Investigate and troubleshoot data and pipeline issues, contributing to root cause analysis and resolution.
  • Participate in code reviews and follow established engineering standards, best practices, and development processes.
  • Contribute to the modernization of data platforms, including cloud migration and adoption of modern data engineering technologies.
  • Document data solutions, pipelines, data flows, and operational processes.
  • Identify opportunities to improve the performance, reliability, scalability, and efficiency of data solutions.

About the Company

Mastercard

Processes payments across a global network

Mastercard operates a global payment network connecting financial institutions, merchants, businesses and consumers. It authorizes, clears and settles transactions between participating institutions, while banks issue Mastercard-branded cards and extend credit to their customers. Its services also include fraud detection, identity verification, payment tokenization, data analysis and consulting for organizations managing commerce and financial operations. The company earns network fees linked to payment volumes and processed transactions, along with fees for its services and solutions. Founded by a group of banks in 1966, Mastercard is headquartered in Purchase, within Harrison, New York.

Company size
10,001+
Company stage
IPO
Headquarters
Town of Harrison, New York
Founded
1966

Recently Posted Jobs

Explore more opportunities at Mastercard

See more jobs