Senior Data Engineering

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 Engineering Overview Ethoca, a Mastercard company, is seeking a Senior Data Engineer to join the First Party Trust (FPT) team. First Party Trust serves Merchants, Financial Institutions (Issuers and Acquirers), and Digital Partners by enabling the identification and mitigation of First Party Fraud across the payment’s ecosystem. The platform leverages modern cloud-based data technologies to ingest, process, secure, enrich, and analyze large-scale transactional and behavioral data. The team develops scalable data pipelines, data products, analytics capabilities, and AI-ready data platforms while ensuring compliance with Mastercard security, privacy, and data governance standards. Our technology stack includes Snowflake, Databricks, Apache Airflow, Apache NiFi, Azure Data Factory (ADF), UDAP, SQL, Python, Spark, Azure Cloud Services, File Transfer Technologies, Splunk, Dynatrace, Terraform, and Data Security Platforms. Are you motivated by solving complex data challenges at enterprise scale? • Do you enjoy building highly scalable and resilient data platforms? • Do you want to leverage cloud-native data technologies to enable analytics, AI, and machine learning solutions? Do you want to be part of a team transforming how global merchants and financial institutions combat fraud through data-driven insights? We are looking for innovative problem-solvers who thrive in a collaborative environment and are passionate about building secure, scalable, and reliable data solutions.

Design, develop, implement, and maintain enterprise-scale data pipelines, data platforms, and analytical data products that support business intelligence, fraud analytics, machine learning initiatives, and operational reporting. Partner with business, product, architecture, and engineering teams to ensure secure, scalable, and compliant data solutions across the organization. Major Accountabilities • Design and develop scalable batch, streaming, and near-real-time data pipelines using modern cloud data engineering technologies. • Build, maintain, and optimize enterprise data platforms leveraging Snowflake, Databricks, Spark, Airflow, NiFi, ADF, and related technologies. • Design and implement robust ETL/ELT frameworks for ingesting, transforming, validating, and delivering data across multiple business domains. • Collaborate with business stakeholders, data consumers, product owners, and architects to understand data requirements and deliver reliable data solutions. • Develop and maintain data models, data marts, and curated datasets that support analytics, reporting, AI, and machine learning use cases. • Integrate and manage data from multiple internal and external sources while ensuring data quality, consistency, lineage, and governance. • Implement data orchestration and workflow automation using Apache Airflow, Azure Data Factory, NiFi, and related technologies. • Develop and optimize Spark and Databricks workloads to process large-scale datasets efficiently. • Monitor and tune data pipelines, database workloads, and platform performance to maximize scalability, reliability, and cost efficiency. • Implement enterprise data governance standards, including data quality controls, metadata management, and lineage tracking. • Ensure compliance with PCI-DSS, privacy regulations, Mastercard security standards, and enterprise data classification requirements. • Implement and maintain