Responsibilities:

• Preferred experience with cloud data platform like Databricks and Snowflake
• Develop and implement a comprehensive data strategy that aligns with the organization's goals.
• Define data architecture standards, principles, and guidelines.
• Responsible for defining and designing the data warehouse, data lakes and establish the data integration strategy.
• Establish data governance policies and procedures and implement data quality assurance processes.
• You will be hands on and work closely to guide a team of Data Engineers in the associated data maintenance, integrations, enhancements, loads and transformation processes for the organization.
• Own and drive the evaluation of data management technologies and lead the implementation with a high bar of performance, scalability, and availability standards.
• Design and optimize the systems for speed, efficiency, and reliability.
• Ensure data security and privacy compliance with relevant regulations and standards.
• Implement security measures to protect sensitive data from breaches and unauthorized access.
• Provide technical guidance and mentorship to junior data engineers and developers.
• Strong data engineering experience in an agile production environment.

Requirements:

• Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale.
• Experience leading the design and implementation of complex features.
• Experience leading a large project and working with other data and software engineers.
• Experience working in enterprise databases and ensure follow industry best practices around data privacy.
• Expertise in using Python or Scala, Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi, Scoop), SQL to build Big Data products & platforms also cloud data platforms like Databricks and Snowflake.
• Experience in Java/.net, Scala, or Python technologies and deliver analytics involving all phases like data ingestion, feature engineering, modelling, tuning, evaluating, monitoring, and presenting.
• Experience in anonymizing data, data product development, analytical models, and AI governance.
• Experience with SQL, Multi-threading, Message Queuing & Distributed Systems.
• Effective communication and collaboration skills to work with both technical and non-technical stakeholders.
• Flexible to work with global offices across several time zones.
• Outstanding problem-solving skills and the ability to navigate complex data challenges

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard's security policies and practices;
• Ensure the confidentiality and integrity of the information being accessed;
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.