Job Title:

Lead Data Platform Engineer

Overview:

Overview:
Are you an experienced data platform engineer with a passion for cloud data innovation and a strong sense of ownership and innovative spirit? The Cloud Data Platforms team is an excellent opportunity for you to design & develop the next wave of data innovation at MasterCard. Our program is leading the efforts to bring our data and analytics expertise into the cloud.

We are looking for a Senior Cloud Platform Engineer to work on creating an AWS Cloud Native Data Platform. You will also work closely with cross-functional teams, including data scientists, data analysts, and software engineers, to help drive data-driven decision making throughout the organization.

The Role:
Developing the AWS Cloud Data Platform using AWS native services and stitching it all together based on the architecture.
Assist in troubleshooting and resolving platform and integration related issues.
Stay up to date with emerging technologies and trends in the data engineering and cloud space and willingness to learn and use new tools and platforms that can improve efficiency.
Work closely with platform engineers, data engineers and architects to make progress.
Follow Agile methodology, take ownership of the assigned tasks and deliver the results in timely manner.

All About You:
• Architect and implement robust data pipelines across large-scale distributed systems using AWS native services.
• Lead the development and maintenance of data platforms leveraging services such as:
• Data & Analytics: AWS Glue, EMR, MSK, Athena, Redshift
• Data Governance: Lake Formation, Glue Catalog
• Storage: S3 (General Purpose and S3 Tables)
• Monitoring: CloudWatch, CloudTrail
• Work hands-on with open table formats including Apache Iceberg and Parquet.
• Design and deploy infrastructure using CloudFormation and Infrastructure as Code (IaC) principles.
• Develop scalable solutions using at least one programming language (e.g., Python, Java).
• Collaborate with cross-functional teams to ensure data integrity, governance, and accessibility.
• Apply knowledge of big data technologies such as Hadoop, NiFi, Kafka, Impala, Hive, Oozie, and Airflow to enhance platform capabilities.
• Utilize data modeling techniques for both SQL and NoSQL systems and apply ETL and data warehousing best practices.
• Contribute to machine learning workflows and analytics using tools like Amazon SageMaker and MWA.
• Proven experience in building and managing data platforms in cloud environments, especially AWS.
• Strong communication and collaboration skills, with the ability to work effectively with data professionals and business stakeholders.
• Detail-oriented with the ability to manage multiple priorities in a fast-paced, deadline-driven environment.
• Bachelor's degree or higher in Computer Science, Information Technology, or a related field.

Nice to have:
Cloud certifications - AWS Data Engineer certification
BI dashboard reporting experiences

To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.