Job Title:
Lead Service Management Engineer
Overview:
Who is Mastercard? We work to connect and power an inclusive, digital economy that benefits everyone, everywhere, by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships, and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation, and delivers better business results.
Overview :
We are seeking a Lead Data Engineer to join Mastercard Architecture & Analytics team. You will help shape our innovation roadmap by exploring new technologies and building scalable, data‑driven prototypes and products. The ideal candidate is hands‑on, curious, adaptable, and motivated to experiment and learn.What You’ll Do* Drive Data Architecture: Own the data architecture and modeling strategy for AI projects. Define how data is stored, organized, and accessed. Select technologies, design schemas/formats, and ensure systems support scalable AI and analytics workloads.* Build Scalable Data Pipelines: Lead development of robust ETL/ELT workflows and data models. Build pipelines that move large datasets with high reliability and low latency to support training and inference for AI and generative AI systems.* Ensure Data Quality & Governance: Oversee data governance and compliance with internal standards and regulations. Implement data anonymization, quality checks, lineage, and controls for handling sensitive information.* Provide Technical Leadership: Offer hands‑on leadership across data engineering projects. Conduct code reviews, enforce best practices, and promote clean, well‑tested code. Introduce improvements in development processes and tooling.* Cross‑Functional Collaboration: Work closely with engineers, scientists, and product stakeholders. Scope work, manage data deliverables in agile sprints, and ensure timely delivery of data components aligned with project milestones.What You’ll Bring* Extensive Data Engineering
All About you - 8–12+ years in data engineering or backend engineering, including senior/lead roles. Experience designing end‑to‑end data systems, solving scale/performance challenges, integrating diverse sources, and operating pipelines in production.* Big Data & Cloud Expertise: Strong skills in Python and/or Java/Scala. Deep experience with Spark, Hadoop, Hive/Impala, and Airflow. Hands‑on work with AWS, Azure, or GCP using cloud‑native processing and storage services (e.g., S3, Glue, EMR, Data Factory). Ability to design scalable, cost‑efficient workloads for experimental and variable R&D environments.* AI/ML Data Lifecycle Knowledge: Understanding of data needs for machine learning—dataset preparation, feature/label management, and supporting real‑time or batch training pipelines. Experience with feature stores or streaming data is useful.* Leadership & Mentorship: Ability to translate ambiguous goals into clear plans, guide engineers, and lead technical execution.* Problem‑Solving Mindset: Approach issues systematically, using analysis and data to select scalable, maintainable solutions.Required Skills*
To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.