Senior Data Engineer
About The Position
Mastercard Foundry is seeking a Senior Data Engineer. In this role, you will take ownership of building and optimizing data platforms, pipelines, and systems that enable advanced analytics, machine learning, and business insights. You’ll collaborate closely with engineering, product, and analytics teams to deliver reliable, production-ready data solutions. Mastercard Foundry is the innovation engine of Mastercard and a hub for new product development. We do this by driving product innovation in emerging technologies and interfaces while focusing on developing a point of view to enhance existing solutions and new use-cases. We also focus on building revenue generating ecosystems and flywheels that can be standalone in adjacent segments and markets. Examples of focus areas include Digital Assets/Stablecoins, Consumer value propositions, Digital payments, Payment Acceptance and Processing, and applications of Artificial Intelligence. This is a hybrid role based in O’Fallon, MO, with an expectation of three days per week onsite.
Requirements
- Experience as a Data Engineer or in a similar role, with strong knowledge of data engineering concepts, methodologies, and modern data architectures.
- Strong hands-on experience with SQL, including writing and optimizing queries for large-scale data processing.
- Strong experience with relational databases, particularly Microsoft SQL Server and related technologies.
- Experience designing, implementing, and maintaining ETL/ELT pipelines and data integration solutions.
- Strong experience with distributed data processing and large-scale data platforms; experience with Databricks and Spark is a plus.
- Experience building and maintaining data lakes, data models, and scalable database solutions for analytics and reporting.
- Knowledge of workflow orchestration and automated end-to-end data pipelines.
- Understanding of data security, governance, compliance, and data quality practices, particularly in enterprise environments.
- Experience with cloud platforms such as AWS, Azure, or GCP and modern data engineering tools.
- Experience with event-driven or streaming architectures and exposure to machine learning or advanced analytics environments is a plus.
- Strong troubleshooting, root cause analysis, critical thinking, and problem-solving skills, with the ability to break down complex technical challenges.
- Ability to manage multiple projects and competing priorities while maintaining high standards for quality, accuracy, and delivery.
- Strong verbal and written communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
- Self-motivated and collaborative team player with the ability to influence technical decisions, mentor engineers, and demonstrate curiosity about emerging technologies and developer productivity tools such as GitHub Copilot.
- Bachelor's degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered.
Nice To Haves
- Experience with Databricks and Spark
- Experience with event-driven or streaming architectures
- Exposure to machine learning or advanced analytics environments
- Curiosity about emerging technologies and developer productivity tools such as GitHub Copilot
Responsibilities
- Design, build, and maintain scalable, reliable data platforms, pipelines, and data products that support analytics, machine learning, and business insights.
- Develop and optimize large-scale batch and streaming data pipelines using modern distributed data processing frameworks.
- Implement workflow orchestration and automation solutions to ensure reliable and efficient data movement and processing.
- Design and integrate data from multiple sources to create accessible, high-quality datasets for business and technical stakeholders.
- Build and maintain modern data lake and data warehousing solutions that support diverse analytical use cases.
- Define and implement scalable data models and database solutions that ensure performance, integrity, and usability.
- Apply data engineering best practices to improve system performance, scalability, resiliency, and maintainability.
- Ensure compliance with data security, governance, privacy, and regulatory requirements.
- Lead technical design discussions and contribute to architecture decisions across data platforms and services.
- Own end-to-end delivery across the SDLC, including requirements, design, development, testing, deployment, and support.
- Troubleshoot production issues, perform root cause analysis, and drive corrective and preventive actions.
- Collaborate with cross-functional teams while mentoring engineers and promoting engineering excellence and knowledge sharing.
Benefits
- insurance (including medical, prescription drug, dental, vision, disability, life insurance)
- flexible spending account and health savings account
- 16 weeks of new parent leave
- up to 20 days of bereavement leave
- 80 hours of Paid Sick and Safe Time
- 25 days of vacation time
- 5 personal days
- 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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
