Senior Data Engineer

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

Level's read on this job

Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Spark, Kafka and Airflow.
Level classifies it as a senior role.
Level lists 967 other open roles at Mastercard.

AI in this role

Builds scalable data platforms and pipelines that support marketing analytics and AI/ML capabilities.

SparkKafkaAirflowAWSSnowflake

data-engineeringetlcloud-migrationdata-governance

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

Overview:

Marketing Services Technology is seeking a Senior Data Engineer to build scalable data platforms, pipelines, and services that power marketing measurement, customer insights, campaign optimization, advanced analytics, and AI/ML capabilities.

This role partners with Product Management, Engineering, Data Science, Analytics, and Business teams to deliver secure, reliable, and high-quality data solutions. The Senior Data Engineer will also contribute to cloud modernization, platform architecture, automation, and operational excellence across the Marketing Services data ecosystem.

Role:

• Design, build, deploy, and maintain scalable batch, streaming, and real-time data pipelines.
• Develop reusable frameworks for data ingestion, transformation, orchestration, and delivery.
• Build and support enterprise data lake, data warehouse, and lakehouse solutions.
• Improve platform scalability, performance, reliability, resiliency, and operational efficiency.
• Implement data quality, observability, governance, security, lineage, and monitoring capabilities.
• Enable reporting, advanced analytics, experimentation, AI/ML, and customer insight use cases.
• Support the migration of legacy platforms to modern cloud-native architectures.
• Establish engineering standards across CI/CD, infrastructure as code, testing, automation, and production support.
• Troubleshoot complex production issues and lead root-cause analysis to improve service reliability.
• Partner with product, engineering, analytics, and business teams to translate requirements into scalable data solutions.
• Mentor engineers and provide technical leadership across data initiatives.
• Contribute to architectural decisions and technology roadmaps for Marketing Services data platforms.

All About You:

• Bachelor’s degree or equivalent experience in computer science, engineering, information systems, or a related technical field.
• Strong experience designing scalable data platforms and distributed data-processing solutions.
• Proficiency in SQL and at least one programming language such as Python, Java, or Scala.
• Experience with technologies such as Spark, Kafka, Hadoop, or comparable large-scale data-processing frameworks.
• Experience building data pipelines for analytics, reporting, machine learning, and operational data products.
• Strong understanding of data modelling, ETL/ELT patterns, data architecture, and data lifecycle management.
• Experience working with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of data governance, security, privacy, lineage, metadata management, and regulatory requirements.
• Experience with Git, CI/CD, DevOps automation, infrastructure as code, testing, deployment, and observability.
• Strong problem-solving skills with experience diagnosing complex issues in distributed environments.
• Ability to balance technical quality with business priorities and customer outcomes.
• Strong communication and collaboration skills across engineering, product, analytics, and business teams.

Preferred Experience:

• Experience leading technical initiatives, influencing architectural decisions, or mentoring engineers.
• Experience modernizing legacy data platforms or supporting cloud migration programmes.
• Exposure to marketing technology, campaign measurement, customer insights, or marketing analytics.
• Advanced degree in a related technical discipline.

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

Atlanta, Georgia: $115,000 - $184,000 USD

How we rate this

Senior Data Engineer at Mastercard rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Data Engineer is an open job at Mastercard.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in Atlanta, Georgia.
The job was posted on September 17, 2026.
Seniority: senior.
Applications are handled by Mastercard. Apply on Mastercard

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringETLCloud MigrationData GovernanceSparkKafkaAirflowAWS

Also common in data engineer jobs at this level

Databricks Airflow Generative AI Snowflake LLM AI agents

Pay

Typical data engineer job: $145k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where cloud migration was part of your work. What did you do?
Tell me about a project where data governance was part of your work. What did you do?
Walk me through how you've used Spark in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Data Engineering, ETL, Cloud Migration, Data Governance, and Spark. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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