Mastercard is hiring a Senior Data Engineer (DC&E) to design, build, and scale cloud-enabled data pipelines and Lakehouse or warehouse platforms that support analytics, BI, regulatory reporting, and data-driven decision making. This hybrid role is based in O'Fallon, MO, with three days per week onsite.

Role Overview

In this position, you will lead end-to-end data engineering activities, from requirements analysis and solution design through coding, testing, deployment, production support, and continuous optimization. You will also help modernize legacy ETL, data warehouse, and analytics workloads by migrating them to cloud-native architectures.

Responsibilities

Design, develop, test, and deploy secure, scalable, high-performance, resilient data pipelines using Apache Spark, Java/Scala, Hadoop, and cloud-native object storage platforms.
Build and maintain batch and near-real-time processing frameworks for petabyte-scale workloads and demanding enterprise requirements.
Create reusable engineering components, frameworks, and design patterns to accelerate data product delivery while meeting enterprise architecture and engineering standards.
Implement “build once, run anywhere” architectures enabling deployment across on-premises and public cloud environments without code changes.
Deliver enterprise data capabilities including data lineage, metadata management, data cataloging, data quality, monitoring, and observability across the data ecosystem.
Partner with architects and platform teams to establish scalable architecture patterns, distributed computing practices, and engineering standards, with an emphasis on adopting modern Lakehouse architectures.
Support cloud modernization initiatives by migrating legacy ETL, data warehouse, and analytics workloads to cloud-native environments using Amazon S3, EMR, and AWS Glue.
Troubleshoot complex production incidents, conduct root cause analysis, and implement sustainable remediation while ensuring alignment with Mastercard security, quality, and operational governance standards.
Mentor engineers through code reviews, technical coaching, knowledge sharing, and best practices, including performance and automation improvements.
Collaborate with product owners, analysts, architects, and business stakeholders to translate requirements into scalable solutions and deliver committed outcomes within established timelines.

Required Qualifications

Hands-on experience as a Data Engineer or Senior Data Engineer delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.
Proven delivery of multiple end-to-end data engineering initiatives in 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 with orchestration and workflow solutions using Apache Airflow, Apache NiFi, or comparable enterprise scheduling and workflow frameworks.
Strong SQL skills and experience with relational and NoSQL databases, including Oracle, SQL Server, Cassandra, and DynamoDB.
Working knowledge of cloud platforms, preferably AWS, including Amazon S3, EMR, and AWS Glue.
Understanding of security, privacy, regulatory, and compliance requirements for sensitive financial and customer data.
Ability to lead complex technical initiatives across multiple teams and influence engineering direction without direct authority.
Demonstrated capability to mentor engineers and raise technical performance through design guidance, knowledge sharing, and constructive feedback.
Excellent communication and stakeholder management, including the ability to explain technical concepts, trade-offs, risks, dependencies, and recommendations to both technical and business audiences.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline (or equivalent practical experience).

Technology Focus

Apache Spark
Java
Scala
Hadoop
Apache Airflow
Apache NiFi
Amazon S3
Amazon EMR
AWS Glue
AWS

Compensation

O'Fallon, Missouri: $115,000 - $184,000 USD per year

Benefits

Competitive base salary and may be eligible for an annual bonus or commissions depending on the role.
Insurance (including medical, prescription drug, dental, vision, disability, life insurance).
Flexible spending account and health savings account.
Paid leaves including 16 weeks of new parent leave and up to 20 days of bereavement leave.
80 hours of Paid Sick and Safe Time, 25 days of vacation time, and 5 personal days (pro-rated based on date of hire).
10 annual paid U.S. observed holidays.
401k with a best-in-class company match.
Deferred compensation for eligible roles.
Fitness reimbursement or on-site fitness facilities.
Eligibility for tuition reimbursement.
Eligibility for interns: 56 hours of Paid Sick and Safe Time, jury duty leave, and on-site fitness facilities in some locations.

Corporate Security Responsibility

Abide by Mastercard’s security policies and practices.
Ensure the confidentiality and integrity of the information being accessed.
Report any suspected information security violation or breach.
Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Senior Data Engineer

Job Description