Lead Data Engineer

Mastercard is hiring a Lead Data Engineer in Arlington, United States. Level rates it ; you can apply on Level.

Level's read on this job

Level rates this data engineer role Little AI ●○○○: aI is not part of the work.
Tools and skills the posting cites include Databricks.
Level files it as a lead role.
Level lists 1,100+ other open roles at Mastercard.
The role was posted in the last few days.

AI in this role

databricks

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

Lead Data Engineer

Overview:
Mastercard’s Data Commercialization Platform (DCP) team is seeking a Lead Data Engineer to design, build, and scale cloud-native data and Business Intelligence solutions across a modern multi-cloud data ecosystem.
This role will focus heavily on Databricks, Snowflake, and AWS, building scalable data pipelines, analytics frameworks, and platform capabilities that support enterprise data products. You will also help drive a multi-cloud architecture across AWS and Azure, enabling secure and governed interoperability across platforms, compute engines, and cloud providers.
The ideal candidate combines strong hands-on engineering expertise with technical leadership and can translate complex platform requirements into scalable, reliable, secure, and cost-effective solutions.
This is a hybrid role based in Arlington, VA requiring three days per week onsite.

Role:
• Design and develop cloud-native data and BI solutions using Databricks and Snowflake on AWS.
• Build scalable, high-performance data pipelines and analytics frameworks supporting enterprise data products.
• Drive implementation of multi-cloud architectures across AWS and Azure, including Azure Databricks and ADLS Gen2.
• Enable seamless integration and interoperability across Databricks, Snowflake, AWS services, and Azure services.
• Build and maintain CI/CD pipelines, automation frameworks, and Infrastructure as Code for reliable data platform provisioning and deployment.
• Implement secure and governed access patterns using RBAC, IAM, service principals, and enterprise identity integration.
• Design reusable platform capabilities that enable 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 and sustainable technical solutions.
• Provide technical leadership and mentorship to engineers while driving initiatives from design through implementation.

All About You:
• 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 services such as S3, Glue, EMR, and IAM.
• Advanced proficiency with Apache Spark/PySpark, Delta Lake, SQL, and Python for large-scale data 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 and open data architectures and formats, including Delta Lake and Apache Iceberg.
• Understanding of FinOps, cloud cost optimization, performance, and scalability for large-scale data workloads.
• Proven ability to lead technical design and architecture decisions, drive complex engineering initiatives across teams, and mentor engineers.
• Strong communication and stakeholder management skills, with the ability to clearly articulate technical decisions, trade-offs, risks, and recommendations.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM discipline. Equivalent practical experience will also be considered.

Mastercard is a merit-based, 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. We hire the most qualified candidate for the role. 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 and may be eligible for an annual bonus or commissions depending on the role. The base salary offered may vary depending on multiple factors, including but not limited to location, job-related knowledge, skills, and experience. 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 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; and many more. Mastercard benefits for interns generally include: 56 hours of Paid Sick and Safe Time; jury duty leave; and on-site fitness facilities in some locations. THIS POSTING RELECTS ONE OR MORE CURRENT VACANCIES ON OUR TEAM, AND MASTERCARD INTENDS TO FILL THIS POSITION BY 01/17/2027. If the fill date has passed, Mastercard intends to fill this position as soon as possible.

Pay Ranges

Arlington, Virginia: $161,000 - $266,000 USD

How we rate this

Lead Data Engineer at Mastercard rates 22 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.