Senior Data Engineer at Mastercard

O'fallon, Missouri, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Jun, 26

Salary

184000.0

Posted On

22 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, ETL, Data Pipelines, Alteryx, Apache NiFi, Apache Airflow, Data Integration, Data Normalization, Power BI, Grafana, Data Quality, Analytical Skills, Problem-Solving, Communication, Project Management, Data Visualization

Industry

IT Services and IT Consulting

Description

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 Senior Data Engineer Who is Mastercard? We are the global technology company behind the world’s fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. What is the AI Ops team? The AI Ops team uses AI, machine learning, and data science techniques to detect anomalies, predict impact, and initiate remediation. The team creates insights—in the form of dashboards, reports, and alerts—from operations data and helps stakeholders make data-driven decisions for planning, troubleshooting, or monitoring application health. Overview The Senior Data Engineer for AI Ops designs, builds, and operates analytics and data engineering solutions that provide operational visibility, insight, and proactive intelligence across enterprise infrastructure, applications, and services. This role focuses on integrating data from diverse operational sources, enabling high-quality dashboards and metrics, and supporting AI-driven operational use cases that improve reliability, performance, and decision-making. Key Responsibilities • Design, build, and maintain scalable ETL and data pipelines using tools such as Alteryx, Apache NiFi, Apache Airflow, or similar technologies. • Integrate and normalize data from multiple operational sources, including monitoring platforms, incident and ticketing systems, SLA/SLO reports, surveys, and enterprise data stores. • Develop and maintain analytics and visualizations using tools such as Power BI, Grafana, and related platforms to deliver operational, management, and executive-level insights. • Ensure data quality, consistency, and reliability through validation, monitoring, and continuous improvement of data pipelines. • Translate operational and business questions into measurable indicators, metrics, and dashboards that clearly communicate current state, risks, trends, and improvement opportunities. • Support incident analysis, root cause investigations, and operational reviews through data-driven insights. • Partner with AI Ops, SRE, infrastructure, and software engineering teams to operationalize analytics and enable advanced automation and AI/ML use cases. • Create and maintain technical documentation, operational procedures, and best practices to support governance, scalability, and reuse. All About You: • Analytical, investigative and problem-solving skills • Strategic thinker with ability to derive and translate data analytics to meet business goals • Sound written and verbal communication skills • Project management skills, highly organized with strong attention to detail • Must be able to work independently in developing and mapping out solutions • Must be able to work in a fast paced and dynamic environment, handle multiple tasks, consistently meet established deadlines, and deliver exceptional results • Strong experience in data engineering and analytics, working with structured, semi-structured, and unstructured data. • Hands-on experience with ETL and workflow orchestration tools such as Alteryx, NiFi, Airflow, or equivalent. • Proven ability to build dashboards and visualizations using Power BI, Grafana, or similar tools. • Solid understanding of data quality, monitoring, and operational resilience. • Strong analytical, problem-solving, and communication skills, with the ability to translate complex data into actionable insights. • Experience collaborating across technical and business teams in an operational or enterprise environment. 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. Pay Ranges O'Fallon, Missouri: $115,000 - $184,000 USD Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.

Responsibilities

The Senior Data Engineer will design, build, and operate scalable ETL and data pipelines, integrating and normalizing data from diverse operational sources to enable high-quality dashboards and metrics. This role supports AI-driven operational use cases focused on improving enterprise infrastructure reliability and performance through data insights.