Senior Software Engineer

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 Software Engineer Overview: Mastercard’s Economic Intelligence team is seeking a Senior Software Engineer to design, build, and operate scalable data systems that power our economic intelligence products. This is a hands-on engineering role focused on delivering complex platform capabilities, modernizing data workloads from on-premises Hadoop technologies to Databricks and cloud-based services, and strengthening engineering practices across the team. The Economic Intelligence team develops data products and analytical capabilities that help customers understand consumer spending, evaluate economic conditions, and make informed business decisions. We transform billions of global transaction records into trusted insights used by clients across financial services, retail, and government. You will collaborate with software engineers, data engineers, data scientists, product managers, and data warehouse teams across multiple locations. This is a hybrid role based in Arlington, VA, requiring three days per week onsite. Role: • Design, develop, test, and operate scalable data-processing solutions using Python, SQL, Spark, Hive, Impala, Databricks, and related technologies. • Own complex data platform capabilities from ingestion and transformation through publishing and consumption. • Provide technical leadership for the modernization of on-premises data workloads to Databricks and cloud-based platforms. • Make and document architecture and design decisions that improve scalability, reliability, maintainability, security, and cost efficiency. • Build production-ready pipelines with appropriate testing, data-quality controls, observability, operational documentation, and recovery procedures. • Diagnose and resolve complex performance, reliability, and data-quality issues across distributed systems. • Contribute directly to implementation while guiding technical execution through design reviews, code reviews, and collaborative problem-solving. • Reduce technical debt by balancing near-term product delivery with long-term platform sustainability. • Partner with product managers and data scientists to translate business and analytical requirements into clear, durable technical solutions. • Mentor engineers, share technical knowledge, and help strengthen engineering practices across geographically distributed teams. • Evaluate new tools and approaches based on measurable improvements to delivery speed, platform reliability, developer productivity, or analytical capability. • Participate in production support and continuous improvement of the systems owned by the team. All About You: • Experience modernizing workloads from Hadoop-based environments to cloud or Databricks platforms. • Experience with Hive, Impala, workflow orchestration, data Lakehouse patterns, or cloud object storage. • Advanced SQL expertise, including query optimization and modeling for very large datasets. • Knowledge of data governance, privacy, security, data lineage, and access-control practices. • Experience supporting analytical, economic, financial, or other data-intensive products. • Experience applying machine learning, generative AI, or agent-based capabilities within production systems. • Experience mentoring engineers and influencing