Lead Data Engineer

Mastercard•O'fallon, MO

7d•$140,000 - $231,000•Hybrid

About The Position

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. You will partner closely with Product Management, Risk Analytics, Data Science, Architecture, Engineering, and Business stakeholders to transform complex business needs into scalable technical solutions, simplify access to trusted data, and accelerate innovation across the ECR portfolio. This is a hybrid role based in O’Fallon, MO, requiring three days per week onsite.

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.
Experience with Java-based application development is a strong plus, particularly in environments where data platforms integrate with enterprise applications and services.

Nice To Haves

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline. Equivalent practical experience will also be considered.
Databricks
Apache Spark / PySpark
Hadoop
Delta Lake
SQL and Python
Apache Airflow
Azure Data Services
Kafka / event streaming
GitHub and CI/CD tooling
Cloud-based Data Lakehouse architectures

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.

Benefits

insurance (including medical, prescription drug, dental, vision, disability, life insurance)
flexible spending account and health savings account
16 weeks of new parent leave
up to 20 days of bereavement leave
80 hours of Paid Sick and Safe Time
25 days of vacation time
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