Mastercard is looking to drive its data strategy forward by designing scalable solutions, building high-performance pipelines, and enabling data-driven decision-making.
Requirements
- Expert in SQL development with hands-on experience in Databricks, Snowflake, Python, and PySpark for designing and implementing advanced data engineering solutions.
- Proven experience collaborating with stakeholders and cross-functional teams to understand business requirements and deliver reliable, high-impact cloud data solutions across Azure, AWS, and Cloud Data Warehouse platforms.
- Skilled in architecting and developing scalable, reusable data models, pipelines, and frameworks leveraging Hadoop, NiFi, and modern cloud Data Lake architectures.
- Experienced in planning and executing end-to-end deployments, upgrades, and migrations with minimal disruption to operations, ensuring adherence to best practices in cloud-native and distributed systems.
- SQL, Databricks, Azure/AWS, Cloud Datawarehouse, Hadoop, Python, Pyspark, Nifi & Data Lake.
Responsibilities
- Gather and understand the data engineering requirements based on the product and Engineering specifications.
- Conduct data discovery to build data models, schemas, tables, view, schemas deployment and many more.
- Building appropriate data pipelines in the application to support ETL and automate the pipelines.
- Implement and manage CI/CD pipelines using GitLab and Jenkins, enabling automated testing, deployment, and monitoring of data workflows.
- Build fact tables, conduct analysis and reporting as per needs.
- Conduct data analysis and perform data operations to support business decisions.
- Provide architecture guidelines and support from Data engineering aspects in product development.
Other
- Strong leadership and communication skills, with the ability to guide and mentor data engineering teams, ensuring effective collaboration between technical and non-technical stakeholders.
- Holds a Bachelor’s degree in Computer Science.
- Good understanding of payment networks.
- Skill in identifying new product ideas from data.
- Experience publishing and protecting scientific intellectual property work.
