Lead Software Engineer

Mastercard • Arlington, VA

8d • Hybrid

About The Position

Mastercard’s Portfolio Intelligence program is seeking a Lead Software Engineer to play a pivotal role in the development and scaling of the Mastercard Intelligence Center, Mastercard’s flagship business intelligence offering, with a primary focus on the data and analytics platform. In this role, you will serve as a hands‑on technical lead, partnering closely with multiple backend‑ and data‑focused scrum teams to design, build, and evolve critical platform capabilities. You will provide technical leadership through direct contributions, architectural decision‑making, and the establishment of engineering standards, while offering technical mentorship to other engineers. You will also help guide the platform’s evolution toward emerging technologies and AI‑driven capabilities, fostering a culture of innovation, technical excellence, and continuous improvement. This is a hybrid position based in Arlington, VA, requiring three days per week onsite.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience.
• Experience as a senior or lead software engineer, including:
• Strong backend development skills (Java preferred; C# or Python also acceptable).
• Designing and operating large scale data pipelines, ETL/ELT processes, and data warehousing solutions.
• Hands on experience with Databricks (Spark), Airflow, Snowflake, and core AWS services.
• Building and maintaining CI/CD pipelines with Jenkins and implementing production observability using Splunk (dashboards, alerts, log analysis).
• Proven ability to deliver secure, high quality, and reliable systems within SLA, including code reviews, test automation, and performance tuning.
• Demonstrated capability to lead and mentor engineers and influence architecture across multiple teams.
• Excellent communication, stakeholder management, and documentation skills—able to clearly articulate trade offs, value, and ROI to both technical and non technical audiences.
• Exposure to data governance, data quality, and metadata management practices for analytics platforms.

Nice To Haves

• Experience building or supporting AI/ML capabilities on top of data platforms (e.g., feature pipelines, inference orchestration, model observability).
• Knowledge of microservices, API design, and distributed systems patterns (idempotency, backpressure, retries, circuit breaking).
• Familiarity with performance and cost optimization in Snowflake (e.g., warehouse sizing, caching) and AWS (e.g., storage and compute cost controls)

Responsibilities

• Lead system level design for data pipelines, data services, and backend components supporting a large-scale BI platform.
• Define and evolve architecture, patterns, and engineering standards (coding, testing, observability, security, performance, and cost efficiency).
• Create solution definitions, architecture proposals, and roadmaps, present tradeoffs and recommendations to product leadership and stakeholders.
• Ensure solutions align with security, compliance, and audit requirements and Mastercard standards; integrate these into the SDLC and reviews.
• Conduct/drive design reviews, architecture reviews, and security reviews; ensure readiness and alignment before build.
• Design and build backend services and ETL/ELT data pipelines (Java preferred; C# or Python acceptable).
• Orchestrate workflows with Airflow; implement data transformations at scale (e.g., Databricks / Spark); optimize data models and warehouse usage (Snowflake).
• Implement CI/CD pipelines with Jenkins; maintain code quality via code reviews, unit/integration/performance testing, and automation.
• Instrument services for observability (e.g., Splunk dashboards/alerts); set and monitor SLOs and error budgets; drive incident response and root cause analysis.
• Champion cost, performance, and reliability optimization across AWS services and data platforms.
• Lead delivery across 2+ scrum teams, partnering with product, data, and platform leads to plan and deliver outcomes on time and to SLA.
• Collaborate with Project/Program Managers to scope work, estimate effort/cost, manage risks and dependencies, and track metrics.
• Provide technical mentorship and coaching; elevate team capabilities via brown bag sessions, pairing, and review culture.
• Coordinate with global/offshore contributors; uphold documentation standards and traceability throughout the SDLC.
• Support RFI/RFP evaluations, vendor/technology selection, and proofs of concept for emerging technologies, including AI driven use cases.

Benefits

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level