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Mastercard

Processes payments across a global network

Senior Data Engineer

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

About the Job

Requirements

  • Hands-on experience as a Data Engineer or Senior Data Engineer delivering enterprise-scale data warehouse, data lake, or data lakehouse solutions.
  • Proven experience delivering multiple end-to-end data engineering initiatives within large-scale distributed computing environments.
  • Hands-on experience migrating ETL/ELT, data warehouse, and analytics workloads from on-premises platforms to cloud-native architectures.
  • Strong development experience with Apache Spark, Scala and/or Java, Hadoop ecosystem technologies, and cloud object storage platforms.
  • Experience building orchestration and workflow solutions using Apache Airflow, Apache NiFi, or comparable enterprise scheduling and workflow frameworks.
  • Strong SQL expertise and experience working with relational and NoSQL databases such as Oracle, SQL Server, Cassandra, and DynamoDB.
  • Working knowledge of cloud platforms, preferably AWS, including Amazon S3, EMR, AWS Glue, and other cloud-native data services.
  • Strong understanding of security, privacy, regulatory, and compliance requirements associated with sensitive financial and customer data.
  • Proven ability to lead complex technical initiatives across multiple teams and influence engineering direction without direct authority.
  • Demonstrated ability to mentor engineers and elevate technical capability, including providing design guidance, knowledge sharing, and constructive feedback.
  • 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 deploy secure, scalable, high-performance, and resilient data pipelines using Apache Spark, Java/Scala, Hadoop, and cloud-native object storage platforms.
  • Build and maintain batch and near-real-time data processing frameworks capable of supporting petabyte-scale workloads and demanding enterprise data requirements.
  • Develop reusable engineering components, frameworks, and design patterns that accelerate data product delivery while maintaining enterprise architecture and engineering standards.
  • Design and implement “build once, run anywhere” architectures that enable seamless deployment across on-premises and public cloud environments without requiring code changes.
  • Implement enterprise data capabilities including data lineage, metadata management, data cataloging, data quality, monitoring, and observability across the data ecosystem.
  • Collaborate with architects and platform teams to establish scalable architecture patterns, distributed computing practices, and engineering standards, while driving adoption of modern lakehouse architectures.
  • Contribute to cloud modernization initiatives by migrating legacy ETL, data warehouse, and analytics workloads from on-premises environments to cloud-native architectures using services such as Amazon S3, EMR, and AWS Glue.
  • Lead end-to-end engineering activities, including requirements analysis, solution design, coding, testing, deployment, production support, and continuous optimization.
  • Partner with product owners, analysts, architects, and business stakeholders to translate requirements into high-quality, scalable solutions and deliver committed outcomes within established timelines.
  • Troubleshoot complex production incidents, perform root cause analysis, and implement sustainable remediation strategies while ensuring compliance with Mastercard’s security, quality, and operational governance standards.
  • Mentor and guide engineers through code reviews, technical coaching, knowledge sharing, and best practices, while identifying opportunities to improve performance, automation, monitoring, and engineering efficiency.

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

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