The Lead Cloud Data Engineer will create technical solutions and lead initiatives to evolve our current descriptive analytics into Predictive and Prescriptive Analytics on cloud platforms.

Responsibilities:
• Design and implement new data pipelines, transfers, and compliance infrastructure to support cloud-based data usage.
• Lead data modernization and transformation initiatives for Loyalty Data products, ensuring compliance with regulations like PCI-DSS, GDPR, and On-Soil requirements.
• Identify and develop cloud-native solutions for evolving data-related product requirements.
• Build solutions on cloud data platforms, such as Databricks, following industry standards.
• Collaborate with architects, technical leads, and DBAs to develop data pipelines.
• Stay current with emerging trends in big data and cloud platforms, providing technical leadership to improve Advanced Analytics Platform.
• Work with cross-functional agile teams, including Developers, BI Developers, and Product Owners.
• Collaborate with Product Owners to implement cloud use cases effectively.
• Participate in architectural discussions, iteration planning, and feature sizing.
• Follow Agile processes and contribute to Agile ceremonies.

All About You:
The ideal candidate is passionate about solving complex problems with elegant solutions and has experience improving processes to boost efficiency. You should have a proven track record of leading technology transformations for large, legacy platforms and guiding the migration from on-premises systems to the cloud. Experience in navigating industry standards (e.g., PCI-DSS), data privacy regulations (e.g., GDPR), and security policies is essential.

The ideal candidate has experience with:
• Data platform engineering concepts, architecture design patterns, and industry best practices.
• Cloud data platforms like Databricks.
• Cloud infrastructure, particularly AWS and/or Azure.
• Expert in data engineering techniques.
• Proficiency in Python, Scala, Spark, Hadoop platforms and tools (Hive, Impala, Airflow, NiFi, Sqoop), and SQL to build Big Data products and platforms.
• Developing and deploying production-level data applications and workflows/pipelines, including machine learning systems in Java, Scala, or Python, with full lifecycle involvement-from data ingestion to feature engineering, modeling, and evaluation.
• Designing scalable data migration solutions using cloud and data lake technologies, along with data transformation tools like Airflow and NiFi for data pipeline orchestration and SQL Server SSIS for ETL.
• Cloud security models, encryption strategies, and network layers for hybrid on-prem and cloud environments.
• Curiosity, creativity, and enthusiasm for technology and innovation.
• Strong quantitative and problem-solving skills.
• An ability to multitask with attention to detail.
• Self-motivation, flexibility, and independence in managing your workload.

Location Requirements: This is a hybrid position based in Mastercard's O'Fallon, Missouri location.

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Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

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.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary based on location, experience and other qualifications for the role and may be eligible for an annual bonus or commissions depending on the role. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance), flexible spending account and health savings account, paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave), 10 annual paid sick days, 10 or more annual paid vacation days based on level, 5 personal days, 10 annual paid U.S. observed holidays, 401k with a best-in-class company match, deferred compensation for eligible roles, fitness reimbursement or on-site fitness facilities, eligibility for tuition reimbursement, gender-inclusive benefits and many more.