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
Data Engineer II
Overview:
Ethoca, a Mastercard company, is seeking a Data Engineer with full stack engineering and AI enablement experience to help build scalable data, analytics, application, and AI-ready solutions across our on-premise and cloud technology landscape. This role is part of a small, agile, high-performing team focused on resilient, secure, maintainable, and intelligent platforms that support a high-growth fintech marketplace.
The ideal candidate brings a strong foundation in data engineering, software engineering practices, and analytical problem solving. This role offers the opportunity to contribute across data pipelines, reporting, analytics, APIs, applications, and AI enablement capabilities while working with teams across Ethoca and Mastercard.
Role:
- Contribute to the development and support of ETL/ELT, data movement, streaming and non-streaming data solutions, data warehousing, reporting, analytics, and BI capabilities.
- Help design, build, and support full stack solutions, including frontend experiences, backend services, APIs, reusable data services, operational dashboards, and enterprise integrations.
- Support the development of AI-ready data pipelines and intelligent application features for analytics, machine learning, generative AI, semantic search, and RAG use cases.
- Work with SAP HANA and Snowflake data environments with focus on configuration, data movement, security, reliability, performance, governance, and production readiness.
- Assist with debugging, optimization, automation, and troubleshooting of data, application, API, and cloud/on-premise issues.
- Contribute to CI/CD, testing, deployment, migration activities while helping minimize service impacts.
- Support performance tuning across data pipelines, queries, application services, APIs, and cloud or on-premise resources.
- Partner with architects, analysts, data engineers, application teams, and business stakeholders to deliver agile, data-driven, AI-enabled solutions.
All About You:
- Bachelor’s degree or equivalent experience in computer science, software engineering, data engineering, mathematics, quantitative science, or a related technical field.
- Strong SQL and programming skills, with experience in Python, Java, Node.js, or similar technologies.
- Understanding of data warehousing concepts, data lakes, data modeling, dimensional modeling, data integration, BI environments, and analytics/data processing engines.
- Familiarity with ETL/ELT tools and data movement platforms such as Apache NiFi, Azure Data Factory, Pentaho, Talend, or similar technologies.
- Working knowledge of cloud infrastructure, cloud-native patterns, source control, Git, CI/CD, testing, deployment, monitoring, and production support.
- Familiarity with full stack development concepts, including frontend frameworks, RESTful APIs, authentication, application security, backend services, integration patterns, and operational dashboards.
- Exposure to JavaScript/TypeScript, React, Angular, Docker, Kubernetes, or similar technologies.
- Ability to debug, optimize code, automate routine tasks, and troubleshoot production application and data issues using a structured problem-solving approach.
- Comfortable collaborating across technical and non-technical teams, communicating trade-offs, and contributing to practical delivery decisions.
- Strong problem-solving, communication, collaboration, analytical thinking, ownership mindset, and attention to detail.
AI, Data Governance, and Production Readiness:
- Experience or familiarity with AI-ready data pipelines, ML/generative AI workloads, LLM APIs.
- Understanding of data quality, lineage, governance, privacy, security, responsible AI, MLOps, GenAIOps, deployment, monitoring, and reliable AI data flows.
- Interest in applying AI responsibly to improve data engineering productivity, automation, analytics, decision support, and customer-facing capabilities.
- Ability to support reliable, scalable, secure, and well-governed data pipelines across structured and unstructured data use cases.
- Awareness of production readiness practices, including monitoring, operational reliability, testing, deployment controls, and supportability.
Preferred Experience:
- Experience in banking, e-commerce, credit cards, payment processing, or high-growth fintech environments.
- Exposure to both SaaS and premises-based architectures across enterprise data, application, and integration platforms.
- Understanding of database change management, deployment planning, migrations, upgrades, mitigation planning, and performance tuning across data pipelines, application services, APIs, and cloud resources.
- Experience or familiarity with working in agile delivery environments and partnering with cross-functional teams to deliver production-ready solutions.
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: $91,000 - $140,000 CAD
