Mastercard is looking to design and develop the next wave of data innovation by bringing their data and analytics expertise into the cloud, specifically by creating an AWS Cloud Native Data Platform.
Requirements
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).
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.
Responsibilities
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.
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
Design and deploy infrastructure using CloudFormation and Infrastructure as Code (IaC) principles.
Other
Follow Agile methodology, take ownership of the assigned tasks and deliver the results in timely manner.
Collaborate with cross-functional teams to ensure data integrity, governance, and accessibility.
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.
Cloud certifications - AWS Data Engineer certification
