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Lead Software Engineer

Job in Arlington, Tarrant County, Texas, 76000, USA
Listing for: Mastercard
Full Time position
Listed on 2026-07-18
Job specializations:
  • Software Development
    DevOps, Cloud Engineer - Software, Full Stack Developer, Backend Developer
Salary/Wage Range or Industry Benchmark: 161000 - 266000 USD Yearly USD 161000.00 266000.00 YEAR
Job Description & How to Apply Below

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 Software Engineer

Overview

The Accelerators group under the Business & Market Insights - Platform Engineering program at Mastercard is seeking a Lead Software Engineer to drive high-impact technical initiatives that accelerate delivery, improve platform scalability, and enable innovation across the organization. The Accelerators group is leading from the front in making meaningful contributions that allow the B&MI organization to go “faster.” This team is intentionally agile and flexible, not defined by a single technology stack, domain, or rigid process.

Instead, it is composed of self-starters and self-unblockers who focus on delivering outcomes while continuously improving how those outcomes shape the next phase of platform evolution.

If you’re seeking an opportunity to impact a business unit across platform engineering, Dev Ops, software engineering, and process transformation—while also mentoring and growing others—this position is for you.

This is a hybrid role based in Arlington, VA, requiring three days per week onsite.

Role
  • Make foundational changes to the CI/CD pipelines and practices at Mastercard to improve reliability, address common use cases, and deliver market facing solutions faster
  • Develop reusable engineering patterns, frameworks, and tools that improve developer experience and accelerate delivery across teams.
  • Drive modernization and optimization of SDLC/PDLC practices through intentional AI adoption and AI-first engineering initiatives.
  • Identify and implement process improvements that increase engineering velocity, quality, and operational efficiency.
  • Mentor and guide engineers across Mastercard’s engineering community, promoting best practices and technical excellence.
  • Collate across platform, product, and engineering teams to align technical solutions with business objectives.
  • Contribute to architectural decisions that enable scalability, resilience, and long-term platform evolution.
  • Support Dev Ops and platform engineering initiatives to improve system reliability, automation, and deployment efficiency.
All About You
  • Extensive experience as a Software Engineer, Full-Stack Engineer, or Platform Engineer in fast-paced, collaborative environments.
  • Strong full-stack development experience across modern stacks (e.g., .NET, Java, React, JavaScript, SQL Server, PostgreSQL, or similar technologies)
  • Proven experience designing and building scalable backend services, APIs, and distributed systems.
  • Strong experience in cloud environments (AWS and/or Azure), with hands‑on experience building and deploying cloud-native applications.
  • Deep Dev Ops and platform engineering experience, including CI/CD pipelines (e.g., Jenkins, Git Hub Actions) and deployment automation.
  • Experience with API management, gateway technologies, secrets management, and infrastructure tooling.
  • Strong understanding of Product Development Life Cycle (PDLC) and ability to improve engineering workflows end-to-end.
  • Experience working with large‑scale data systems, including ETL pipelines and high-volume data processing environments.
  • Demonstrated ability to identify and implement engineering efficiency improvements across teams or platforms.
  • Strong interest in AI-enabled engineering, including workflow automation, developer productivity, and SDLC augmentation.
  • Experience working in Agile environments with cross-functional teams and iterative delivery models.
  • Proven ability to lead technical initiatives, manage complex engineering efforts, or drive platform-level improvements.
  • Experience mentoring or coaching engineers and contributing to technical team growth.
  • Strong analytical thinking, problem-solving skills, and…
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