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Economic Intelligence is a Mastercard Services program within Economic & Business Intelligence (EBI). The program delivers macro-to-micro economic and market insights powered by Mastercard data, analytics, and research. Our goal is to help customers understand economic trends, benchmark performance, forecast outcomes, and make informed strategic decisions across geographies and industries. As an engineering team, we analyze billions of transactions globally and build platforms that deliver insights into historical consumer spending, forecasts of future spending, and expert commentary on the current economic climate. Our customers span financial services, retail, and government sectors worldwide. We are actively expanding our platform capabilities and work closely with Data Scientists and Product Managers to deliver reliable, flexible, and scalable solutions.
Job Responsibility:
Lead technical execution to deliver end-to-end capabilities from data processing through publishing and customer consumption
Design, build, and evolve scalable, maintainable data pipelines that deliver insights from economic data
Drive performance, reliability, observability, and readability in the data platform codebase
Own and unify the data layer across multiple products, establishing shared patterns, reusable components, and clear interfaces
Translate business needs into durable technical designs
Tackle technical debt strategically
Set engineering direction and standards for pipeline development and cross-team integration
Write, test, and review code
Provide technical leadership through mentorship, rigorous code reviews, and support for other engineers’ growth and delivery
Continuously innovate, evaluating new approaches, tools, and technologies
Requirements:
Strong professional experience with Python building production-grade systems
Strong SQL skills, including writing readable and well-tuned queries for large-scale datasets
Experience leading design and delivery of data pipelines and/or data platform components, with attention to scalability, reliability, and maintainability
Familiarity with Databricks (or similar Spark-based data platforms)
Comfortable using LLM‑based coding tools
Strong foundation in object-oriented software design and engineering best practices
Comfortable with Linux command line and production troubleshooting
Clear communicator with strong written and verbal English
Ownership mindset: motivation, creativity, self-direction, and ability to thrive in small, collaborative teams while influencing across boundaries
Passion for analytical/quantitative problem solving, quality, and continuous improvement of both platform and team processes
Nice to have:
Experience with C# or another strongly-typed object-oriented language, and ability to collaborate effectively with .NET/React engineers on integration points between pipelines and publishing/UI systems