Lead Data Engineer

Mastercard's Enterprise Credit Risk (ECR) team is seeking a Lead Data Engineer to design and scale the next generation of data platforms that power credit decisioning, portfolio risk management, regulatory reporting, analytics, and AI-driven insights across Mastercard's lending and risk ecosystems.

In this role, you will combine deep hands-on data engineering expertise with technical leadership to build reliable, scalable, governed, and high-quality data products. You will lead the architecture and implementation of modern data engineering solutions across cloud platforms, large-scale data processing, data governance, and operational excellence.

Responsibilities:

• Lead the design, development, and evolution of enterprise-grade data platforms and pipelines supporting credit risk products, decisioning capabilities, analytics, and regulatory reporting.
• Architect and implement scalable ETL/ELT frameworks using Databricks, Apache Spark, Delta Lake, and cloud-native technologies to support high-volume data workloads.
• Drive data platform modernization and cloud transformation, including the migration of legacy data assets to modern cloud-based and Data Lakehouse architectures.
• Establish and advance data quality, lineage, metadata, governance, observability, and monitoring capabilities to deliver trusted, compliant, and reliable data products.
• Partner across Risk, Product, Data Science, Architecture, Engineering, and Business teams to translate complex requirements into scalable, sustainable technical solutions.
• Define and promote engineering standards and best practices across coding, testing, data quality, deployment automation, documentation, and operational excellence.
• Lead technical design reviews and influence architectural decisions for data-intensive applications, platforms, and services.
• Optimize large-scale data workloads and platforms for performance, reliability, scalability, resiliency, and cost efficiency.
• Build reusable, governed data products and capabilities that enable AI, machine learning, advanced analytics, and emerging risk use cases.
• Drive technical initiatives from strategy through execution, identifying dependencies, managing technical risks, and ensuring solutions align with business priorities and long-term platform strategy.
• Mentor and coach engineers across the organization, providing technical guidance, design expertise, knowledge sharing, and feedback to strengthen engineering capabilities.
• Shape technology roadmaps and delivery priorities across the ECR portfolio, balancing business value, engineering feasibility, risk, compliance, and long-term platform sustainability.
• Ensure engineering solutions meet security, privacy, regulatory, compliance, and audit requirements through appropriate controls, documentation, and engineering practices.
• Create clarity in complex and ambiguous environments, communicate technical trade-offs to senior stakeholders, and foster a culture of ownership, accountability, and continuous improvement.

Requirements:

• Deep expertise in designing and implementing large-scale data engineering solutions and distributed data processing systems.
• Advanced proficiency with Databricks, Apache Spark/PySpark, Delta Lake, SQL, and Python.
• Experience building and operating cloud-based data platforms using Azure, AWS, or GCP.
• Strong experience developing enterprise-grade ETL/ELT pipelines, data integration frameworks, and streaming architectures.
• Strong understanding of data modeling and data architecture for analytical and operational workloads.
• Experience implementing data quality, lineage, metadata management, observability, and data governance frameworks in enterprise environments.
• Experience working with modern data formats and storage technologies, including Parquet, Avro, and ORC.
• Working knowledge of CI/CD, infrastructure-as-code, automated testing, Git/GitHub, and DevOps practices for data engineering environments.
• Experience with workflow orchestration tools, such as Apache Airflow.
• Strong understanding of security, privacy, regulatory, and compliance requirements associated with sensitive financial and customer data.
• Proven ability to lead complex technical initiatives across multiple teams and influence engineering direction without direct authority.
• Demonstrated ability to mentor engineers and elevate technical capability, including providing design guidance, knowledge sharing, and constructive feedback.
• Excellent communication and stakeholder management skills, with the ability to clearly articulate technical concepts, trade-offs, risks, dependencies, and recommendations to both technical and business audiences.

Benefits:

• Insurance (including medical, prescription drug, dental, vision, disability, life insurance)
• Flexible spending account and health savings account
• Paid leaves (including 16 weeks of new parent leave and up to 20 days of bereavement leave)
• 80 hours of Paid Sick and Safe Time
• 25 days of vacation time and 5 personal days, pro-rated based on date of hire
• 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