Senior Data Engineer — Cloud Data Pipelines & Lakehouse

Mastercard; Helena (MT); On-site; USD 130,000 - 190,000; Full time

Job summary

Mastercard is seeking a Senior Data Engineer to design, build, and scale data pipelines powering its enterprise data warehouse and lakehouse environments. You will work across on-premises and cloud platforms, leveraging Spark, Java/Scala, Airflow, and AWS services to deliver high-performance, reliable data products and analytics capabilities.

You will mentor engineers, drive end-to-end delivery, and partner with product owners, analysts, and stakeholders to meet business needs while upholding

Qualifications

• 7+ years of experience delivering enterprise-scale Data Warehouse, Data Lake, or Data Lakehouse solutions.
• Proven experience implementing multiple end-to-end data engineering projects within large-scale distributed computing environments.
• Hands-on experience migrating ETL and analytics workloads from on-premises platforms to cloud-native environments.

Responsibilities

• Design, develop, test, and deploy high-quality, secure, scalable data pipelines using Apache Spark, Java/Scala across Hadoop and cloud-native object storage platforms.
• Design and implement architecture to support deployment across on-premises and public cloud environments without code changes.
• Migrate ETL and data warehouse workloads from on-premises to cloud-native architectures and leverage cloud services to improve scalability and reliability.
• Lead end-to-end development activities, mentor junior engineers, and collaborate with product owners and stakeholders to deliver high-quality solutions.
• Troubleshoot production incidents, ensure governance and security, and drive automation and observability improvements.

Skills

Apache Spark

Scala/Java

Hadoop

Object Storage

Airflow/NiFi

SQL

NoSQL

AWS

Tools

Airflow

NiFi

Oracle

SQL Server

Cassandra

DynamoDB

EMR

S3

Glue

Job description

Mastercard is seeking a Senior Data Engineer to design, build, and scale data pipelines powering its enterprise data warehouse and lakehouse environments. You will work across on-premises and cloud platforms, leveraging Spark, Java/Scala, Airflow, and AWS services to deliver high-performance, reliable data products and analytics capabilities.

You will mentor engineers, drive end-to-end delivery, and partner with product owners, analysts, and stakeholders to meet business needs while upholding