Senior Data Engineer
Mastercard16 days ago
Base Salary
$115k - $184k/yr
Responsibilities
- Design, build, and maintain scalable data platforms, pipelines, and data products for analytics, machine learning, and business insights.
- Develop and optimize large-scale batch and streaming data pipelines using distributed data processing frameworks.
- Implement workflow orchestration, automation, and end-to-end data movement solutions.
- Integrate data from multiple sources and build high-quality datasets, data lakes, warehouses, data models, and database solutions.
- Apply data engineering practices to improve performance, scalability, resiliency, maintainability, data quality, and compliance.
- Lead technical design discussions and contribute to architecture decisions across data platforms and services.
- Own requirements, design, development, testing, deployment, and support across the software development lifecycle.
- Troubleshoot production issues, perform root cause analysis, and drive corrective and preventive actions.
- Collaborate with cross-functional teams, mentor engineers, and promote engineering excellence and knowledge sharing.
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 SQL experience, 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.
- Experience with distributed data processing and large-scale data platforms; Databricks and Spark experience 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 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, problem-solving, communication, collaboration, mentoring, and prioritization skills.
- Bachelor’s degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field; equivalent practical experience may also be considered.
Benefits
- Hybrid role based in O’Fallon, Missouri, with an expectation of three days per week onsite.
- Full-time benefits generally include medical, prescription drug, dental, vision, disability, and life insurance; flexible spending and health savings accounts; paid leave; vacation and personal days; paid holidays; 401(k) matching; fitness reimbursement or onsite fitness facilities; and tuition reimbursement.
- The position is intended to be filled by November 18, 2026, or as soon as possible if that date has passed.
Tech Stack
Categories
Data Engineering
About Mastercard
Mastercard builds and operates a global payments network used by banks, merchants, fintechs, and governments, offering card processing, real-time payments, tokenization, and fraud/risk services. It generates revenue from transaction processing and assessment/service fees across more than 200 countries and territories. Founded in 1966 and headquartered in Purchase, New York, Mastercard is a public company listed on the NYSE (ticker: MA).