Senior Data Engineer

MasterCard; O’Fallon (MO); On-site; USD 115,000 - 184,000; Full time

Benefits offered by this job

Health insurance

401k with match

Paid time off

Job summary

Mastercard seeks a Senior Data Engineer to design, build, and scale its next-generation Data Quality platform. You will create scalable data pipelines using Spark, Databricks, Python/Scala/Java, and AWS, collaborating with Data Strategists, Product Owners, Architects, and Engineering teams to improve trust and usability of enterprise data assets.

You will apply AI/ML techniques for anomaly detection, support production systems, and contribute to architecture standards while driving innovation

Qualifications

• Advanced experience designing and developing scalable data pipelines using Spark, Scala, Python, Java, Databricks, and AWS Services.
• Strong expertise in data engineering, data quality frameworks, data warehousing, ETL/ELT processes, Nifi and large-scale distributed data processing environments.
• Strong SQL skills with Oracle, PostgreSQL, Iceberg, Ozone, Hadoop, and object storage.
• Experience implementing data quality controls, validation frameworks, observability, monitoring, and incident resolution.

Responsibilities

• Design, develop, and maintain scalable, high-performance data pipelines and data quality frameworks.
• Collaborate with Data Strategists, Data Stewards, Product Owners, Architects, and Engineering teams.
• Develop and optimize data processing solutions using AWS, SQL, data warehouses, and data lakes.
• Apply AI/ML techniques for data quality monitoring and anomaly detection.
• Provide production support and resolve data incidents; ensure platform reliability.

Skills

Spark

Scala

Python

Java

Databricks

AWS Services

Data Quality

Big Data

SQL

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Mathematics, or a related technical field

Cloud, data engineering, big data, AI/ML, or analytics certifications

Tools

Nifi

Oracle

PostgreSQL

Iceberg

Ozone

Hadoop

Job 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? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview

The Enterprise Data Quality team is seeking a Senior Data Engineer to help build and scale Mastercard's next-generation Data Quality platform. This role focuses on designing and developing high-performance data pipelines, data quality frameworks, and cloud-native data solutions that improve trust, reliability, and usability of enterprise data assets. The ideal candidate is passionate about solving complex data challenges, leveraging modern big data technologies, and driving continuous innovation in a fast-paced, collaborative environment.

Role

• Design, develop, and maintain scalable, high-performance data pipelines using Spark, Scala/Python/Java, Databricks, Hadoop, and cloud-native technologies to support enterprise data and analytics platforms.
• Partners with Data Strategists, Data Stewards, Product Owners, Architects, and Engineering teams to solve complex data challenges and deliver enterprise data quality and data engineering solutions.
• Implement and support data quality frameworks, validation controls, monitoring, observability, and automated remediation capabilities to improve data trust, reliability, and business outcomes.
• Develop and optimize data processing solutions using AWS services, SQL, data warehouses, and data lakes while ensuring performance, scalability, security, and operational excellence.
• Apply AI/ML techniques, anomaly detection, predictive analytics, and statistical modeling to enhance data quality monitoring, intelligent threshold recommendations, alert reduction, and root cause analysis.
• Perform production support, troubleshoot complex data issues, conduct root cause analysis, and independently resolve incidents while maintaining platform stability and service reliability.
• Contribute to architecture, engineering standards, and continuous innovation by evaluating emerging technologies, Generative AI capabilities, and best practices that improve data quality, developer productivity, and operational efficiency.

All About You

Essential Knowledge, Skills, and Experience

• Have advanced experience designing and developing scalable data pipelines using Spark, Scala, Python, Java, Databricks, and AWS Services.
• Possess strong expertise in data engineering, data quality frameworks, data warehousing, ETL/ELT processes, Nifi and large-scale distributed data processing environments.
• Demonstrate advanced SQL skills and experience working with technologies such as Oracle, PostgreSQL, Iceberg, Ozone, Hadoop, and object storage platforms.
• Have experience implementing data quality controls, validation frameworks, observability, monitoring, and incident resolution processes to improve data reliability and trust.
• Be a strong communicator and collaborator, capable of working effectively with Data Strategists, Data Stewards, Product Owners, Architects, and Engineering teams to deliver business outcomes.

Desirable or Additional Capabilities

• Experience applying Artificial Intelligence (AI), Machine Learning (ML), statistical modeling, and anomaly detection techniques to data quality, monitoring, and operational efficiency use cases.
• Familiarity with Deep Learning concepts, predictive analytics, pattern recognition, and AI/ML frameworks such as TensorFlow, PyTorch, or similar technologies.
• Experience leveraging Generative AI and AI-assisted development tools to improve engineering productivity, automate processes, accelerate delivery, and enhance solution quality.
• Demonstrate intellectual curiosity, a growth mindset, and a passion for continuous learning, innovation, and evaluating emerging technologies to solve complex business and data challenges.

Education

• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Mathematics, or a related technical field, or equivalent practical experience.
• Relevant cloud, data engineering, big data, AI/ML, or analytics certifications are a plus.

#LI-FT1

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 [e-mail] 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
• 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.