Description
Mastercard's Marketing Services Technology team is seeking a Senior Data Engineer to design, build, and maintain scalable data platforms, pipelines, and services. As a Senior Data Engineer, you will partner with cross-functional teams to deliver secure, reliable, and high-quality data solutions that power marketing measurement, customer insights, campaign optimization, and advanced analytics.
Key responsibilities:
- Design, build, deploy, and maintain scalable batch, streaming, and real-time data pipelines
- Develop reusable frameworks for data ingestion, transformation, orchestration, and delivery
- Build and support enterprise data lake, data warehouse, and lakehouse solutions
- Improve platform scalability, performance, reliability, resiliency, and operational efficiency
- Implement data quality, observability, governance, security, lineage, and monitoring capabilities
- Enable reporting, advanced analytics, experimentation, AI/ML, and customer insight use cases
- Support the migration of legacy platforms to modern cloud-native architectures
- Establish engineering standards across CI/CD, infrastructure as code, testing, automation, and production support
- Troubleshoot complex production issues and lead root-cause analysis to improve service reliability
- Mentor engineers and provide technical leadership across data initiatives
- Contribute to architectural decisions and technology roadmaps for Marketing Services data platforms
Requirements:
- Bachelor's degree or equivalent experience in computer science, engineering, information systems, or a related technical field
- Strong experience designing scalable data platforms and distributed data-processing solutions
- Proficiency in SQL and at least one programming language such as Python, Java, or Scala
- Experience with technologies such as Spark, Kafka, Hadoop, or comparable large-scale data-processing frameworks
- Experience building data pipelines for analytics, reporting, machine learning, and operational data products
- Strong understanding of data modelling, ETL/ELT patterns, data architecture, and data lifecycle management
- Experience working with cloud platforms such as AWS, Azure, or GCP
- Knowledge of data governance, security, privacy, lineage, metadata management, and regulatory requirements
- Experience with Git, CI/CD, DevOps automation, infrastructure as code, testing, deployment, and observability
- Strong problem-solving skills with experience diagnosing complex issues in distributed environments
- Ability to balance technical quality with business priorities and customer outcomes
- Strong communication and collaboration skills across engineering, product, analytics, and business teams
Benefits:
- Insurance (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
- 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