Principal Big Data Engineer

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Principal Big Data Engineer

Overview:
Loyalty Rewards & Segments Program is looking for a Principal Data Engineer to lead the development of Predictive and Prescriptive Analytics solutions. In this role, you will enable merchants and issuers to offer seamless loyalty rewards, including points, miles, or cash-back benefits to cardholders worldwide.

As a Principal Data Architect, you will design and lead efforts to evolve the existing descriptive analytics into advanced Predictive and Prescriptive Analytics on cloud platforms. This includes creating innovative, data-driven solutions to meet business and customer needs, while enabling data-informed decisions. You’ll achieve this by building machine learning models, automating data pipelines, designing data architectures and schemas, and processing large volumes of data using tools and technologies such as NiFi for data pipelines, Python and TensorFlow for machine learning, Spark for distributed data processing, and R for statistical analysis, along with Data Intelligence platforms like Databricks for scalable big data analytics.

Role:
The Principal Architect serves as a technical leader for Loyalty products, overseeing multiple functional areas. You will collaborate with the Loyalty Engineering team to define and execute the technical roadmap, particularly focusing on the strategy for Predictive and Prescriptive Analytics. This will require you to define the strategy, plan its execution, and work with key stakeholder groups, such as Information Security, Data Privacy, and Mastercard’s Architecture & Technology team, to ensure alignment with internal, legal, and industry standards. Additionally, you will guide internal development teams through the entire Software Development Lifecycle, from gathering requirements and performing technical design to building and delivering new capabilities.

Responsibilities:
• Drive the development of products and platforms with a focus on Machine Learning and Data Engineering.
• Design secure, reliable, and scalable solutions that incorporate both functional and non-functional requirements from product teams, security teams, and technology stakeholders. Present these solutions for review within Loyalty Products and to the wider Mastercard Architecture & Technology Architecture Review Team.
• Define the technical strategy for Loyalty Data and Predictive Analytics, contributing to long-term goals, roadmaps (12-18 months), and detailed planning at quarterly and sprint levels.
• Lead modernization efforts and data transformation solutions for Loyalty Data products, ensuring compliance with payment standards and regulations like PCI-DSS, GDPR, and local On-Soil requirements.
• Collaborate with technical leads, data stewards, DBAs, and database developers to support large-scale, like-for-like data migrations.
• Stay informed about emerging trends and best practices in big data and cloud platforms, providing technical leadership to enhance the quality of data platforms continuously.
• Work closely with teams like Data Privacy, Information Security, Cryptographic Architecture, and Business Operations to gather requirements and ensure compliance with Mastercard policies, industry standards, and regulations.
• Translate business requirements into technical specifications involving data streams, integrations, transformations, databases, and data warehouses.
• Define the framework, standards, and principles for data architecture, covering areas such as modeling, metadata, security, and reference data.
• Evaluate and recommend the best analytics solutions, considering usability, technical feasibility, timelines, and stakeholder needs.
• Break down large solutions into smaller, achievable milestones to gather feedback and data from product managers and stakeholders.

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.

Requirements:
• Expertise in data platform engineering concepts, architecture design patterns, and industry best practices.
• Subject matter expertise in Databricks and experience in cloud infrastructure, particularly AWS and/or Azure.
• Advanced statistical analysis, coding, and data engineering techniques.
• Open-source tools, predictive analytics, machine learning, and advanced statistics for basic analytical tasks.
• Proficiency in Python, Scala, Spark, Hadoop platforms and tools (Hive, Impala, Airflow, NiFi, Sqoop), and SQL to build Big Data products and platforms.
• Experience 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.
• Architecting 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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#AI

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.