Lead Data Engineer

Mastercard’s Data Commercialization Platform (DCP) team is building cloud-native capabilities to help turn enterprise data into business-ready insights across a modern multi-cloud environment. As a Lead Data Engineer, you will design, build, and scale data and Business Intelligence solutions, with a focus on Databricks, Snowflake, and AWS, while also helping shape multi-cloud architectures across AWS and Azure. This hybrid role is based in Arlington, VA with three days per week onsite.

In this position, you will help deliver governed interoperability across multiple platforms, compute engines, and cloud providers, while leading technical decisions, standards, and engineering execution from design through implementation.

What you’ll do

• Design and develop cloud-native data and BI solutions using Databricks and Snowflake on AWS.
• Build scalable, high-performance data pipelines and analytics frameworks that support enterprise data products.
• Drive multi-cloud architectures across AWS and Azure, including Azure Databricks and ADLS Gen2.
• Enable seamless integration across Databricks, Snowflake, AWS, and Azure services.
• Build and maintain CI/CD pipelines, automation frameworks, and Infrastructure as Code for reliable provisioning and deployment.
• Implement secure, governed access patterns using RBAC, IAM, service principals, and enterprise identity integration.
• Create reusable platform capabilities that support data interoperability across multiple compute engines and cloud providers.
• Establish engineering standards for development, testing, deployment, monitoring, documentation, and operational excellence.
• Optimize data platforms and workloads for performance, scalability, reliability, resiliency, and cost efficiency.
• Lead technical design reviews and influence architecture and platform engineering decisions.
• Partner with Product, Architecture, Engineering, Data, and Business teams to translate complex requirements into scalable technical solutions.
• Provide technical leadership and mentorship to engineers while driving initiatives from design through implementation.

What you bring

• Deep hands-on experience as a Lead or Senior Data Engineer designing and building enterprise-scale cloud data, analytics, and BI platforms.
• Strong expertise with Databricks, Snowflake, and AWS, including AWS S3, AWS Glue, AWS EMR, and AWS IAM.
• Advanced proficiency with Apache Spark/PySpark, Delta Lake, SQL, and Python for large-scale processing and analytics.
• Experience building scalable ETL/ELT pipelines, data integration frameworks, and distributed data solutions.
• Experience designing multi-cloud data architectures and integrations across AWS and Azure; experience with Azure Databricks and ADLS Gen2 is a plus.
• Strong experience with CI/CD, Infrastructure as Code, automation, Git/GitHub, and DevOps practices for data platforms.
• Experience implementing enterprise security, governance, and access controls, including RBAC, IAM, service principals, data lineage, metadata management, and observability.
• Knowledge of modern open data architectures and formats, including Delta Lake and Apache Iceberg.
• Understanding of FinOps, cloud cost optimization, performance, and scalability for large-scale workloads.
• Proven ability to lead technical design and architecture decisions, drive complex initiatives across teams, and mentor engineers.
• Strong communication and stakeholder management skills, with the ability to articulate technical decisions, trade-offs, risks, and recommendations.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related STEM discipline, or equivalent practical experience.

Tools and technologies

• Databricks, Snowflake
• AWS, Azure, Azure Databricks, ADLS Gen2
• AWS S3, AWS Glue, AWS EMR, AWS IAM
• Apache Spark, PySpark, Delta Lake, SQL, Python
• CI/CD, Infrastructure as Code, Git, GitHub
• RBAC, service principals, data lineage, metadata management, observability, Apache Iceberg

Compensation and location

• Location: Arlington, VA (hybrid, three days per week onsite)
• Pay range (Arlington, Virginia): USD 161,000 - 266,000 per year

Benefits

• Competitive base salary
• Annual bonus or commissions (depending on the role)
• Insurance including medical, prescription drug, dental, vision, disability, and 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 best-in-class company match
• Deferred compensation for eligible roles
• Fitness reimbursement or on-site fitness facilities
• Eligibility for tuition reimbursement

Corporate security responsibility

• 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.
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.