Data Engineer, Mastercard
CA$91-140k
Global payments technology company
Posted today
Global payments technology company
1001+ employees
Posted today
CA$91-140k
1001+ employees
Company mission
To connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.
Role
Who you are
- 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
- 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
Desirable
- 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
What the job involves
- 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
Our take
Mastercard is in the global payments business, and operates the world's fastest payments processing network. Its products and solutions have become central to everyday commerce across the world, in activities ranging from shopping and travelling to running businesses.
As the economy has become more and more digitized, Mastercard has been a leading player in helping businesses and individuals across the globe embrace card payments and digital banking. One of the world's largest companies, its revenue has seen consistent gain in the last 20 years.
The challenge for modern payments companies is that payments are always changing, as seen in the astronomical rise of contactless payments over the last decade. Mastercard's acquisition of blockchain systems, and an overall focus on leveraging its technology towards a digital economy, has placed the company in good stead to keep up to date with current trends, like cryptocurrency, in the digitized payments world.
Steph
Company Specialist at Welcome to the Jungle
Insights
21% employee growth in 12 months
Company
Company HQ
Purchase, Harrison, NY
Leadership
Michael Miebach
(CEO)Michael has served in a variety of roles at the company, including President and CPO. They are currently a Board Member at IBM, Accion, the World Resources Institute, the US-India Strategic Partnership Forum, and the Metropolitan Opera. They are also a Trustee of USCIB.
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