Lead Data 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 Lead Data Engineer Overview: Ethoca is seeking a Lead Data Engineer to drive on-premise solutions and Azure cloud enablement while advancing big data, AI-enabled, and full stack capabilities across our technology landscape. This is a highly visible role within a high-performing team, responsible for delivering scalable, intelligent, and resilient solutions that support a rapidly growing fintech business. The successful candidate will bring expertise in cloud, data engineering, software development, and AI/ML technologies, partnering across Ethoca and Mastercard to design and implement production-ready data platforms, applications, APIs, and AI-enabled solutions. Role: • Lead the development of ETL/ELT processes, data movement, streaming and batch data solutions, and enterprise analytics capabilities. • Design, build, and support scalable applications, APIs, services, user interfaces, and AI-enabled solutions. • Drive data lake and cloud initiatives while supporting large-scale data platforms in Azure and on-premise environments. • Maintain and enhance SAP HANA-based data warehouse environments with a focus on reliability, security, scalability, and performance. • Partner with product, analytics, architecture, and engineering teams to translate business requirements into production-ready data, AI, and application solutions. • Support deployments, migrations, upgrades, automation initiatives, and production operations. • Contribute to the evolution of cloud architecture, development standards, and engineering best practices. All About You: • Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline. • Demonstrated experience designing and delivering enterprise-scale data warehouse and data lake solutions. • Strong data modelling, data integration, and SQL expertise. • Advanced programming skills with exposure to Java, JavaScript, Python, R, or similar technologies. • Experience designing and supporting large-scale data platforms, applications, and distributed systems. • Strong understanding of cloud infrastructure and automation, preferably within Azure environments. • Hands-on experience with full stack development, including APIs, backend services, application logic, and user interface development. • Experience with data integration tools such as Apache NiFi, Azure Data Factory, Pentaho, Talend, or similar platforms. • Knowledge of streaming data technologies such as Kafka and analytics engines such as Spark or Storm. • Experience working with Git, source control, CI/CD, deployment pipelines, and DevOps practices. • Strong troubleshooting, performance tuning, and problem-solving capabilities. • Experience applying AI and machine learning techniques to solve business problems and support intelligent decision-making. • Familiarity with AI-enabled applications, model-driven services, automation, and production ML deployments. • Excellent communication skills with the ability to collaborate effectively across technical and business teams. • Experience operating within highly regulated, security-focused environments, including PII and PCI-DSS requirements. Preferred Experience: • Experience within banking, payments, fintech, e-commerce, or credit card industries is highly desirable. • Exposure to both SaaS and on-premise architectures, along with experience supporting SAP HANA or Teradata environments, will be considered a strong asset. Mastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact [email protected] and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program. This posting reflects one or more current openings on our team. Pay Ranges Toronto, Canada: $127,000 - $203,000 CAD

The Lead Data Engineer will design and implement scalable data platforms, applications, and AI-enabled solutions while driving cloud enablement initiatives. They will also maintain SAP HANA-based data warehouse environments and collaborate with cross-functional teams to translate business requirements into production-ready solutions.

Candidates must hold a bachelor's degree in a technical discipline and possess extensive experience in enterprise-scale data warehousing and cloud infrastructure. Strong proficiency in programming, data integration tools, and AI/ML techniques is required to support high-performance fintech operations.

• Discretionary annual incentive program

• Microsoft AzurePreferred
• SQLPreferred
• CI/CDPreferred
• Machine learningPreferred
• JavaScriptPreferred
• JavaPreferred
• PythonPreferred

Identified from the job description. Confirm important requirements above.

• Data engineering
• Azure
• Cloud architecture
• ETL/ELT
• Data modeling
• SQL
• Java
• JavaScript
• Python
• R
• Apache NiFi
• Azure Data Factory
• Kafka
• Spark
• CI/CD
• Machine learning
• Data Lakes
• Solutions Support
• Full Stack Development
• Business Problems
• Pipelines
• Financial Technology (FinTech)
• Git (Version Control System)
• Resilience
• Product Analytics
• Enterprise Analytics
• Java (Programming Language)
• JavaScript (Programming Language)
• Application Programming Interface (API)
• Artificial Intelligence
• Business Logic
• Software Development
• Automation
• Microsoft Azure
• Big Data
• Business Requirements
• Decision Making
• Software As A Service (SaaS)
• Cloud Computing Architecture
• Cloud Infrastructure
• Version Control
• Communication
• Computer Science
• Confidentiality
• Corporate Security
• Data Engineering
• Data Integration
• Extract Transform Load (ETL)
• Data Modeling
• Data Warehousing

• Data & Analytics
• Software
• Engineering
• Technology
• Finance & Accounting
• Lead Data Engineer
• Data Engineer
• Software Developers
• Database Administrators

Minimum education

Bachelor’s degree

Minimum experience

5+ years

Posting language

English

Working hours

40 hours per week