Lead Data Engineer

Our Purpose

We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.

Title and Summary

Lead Data Engineer

Overview: 

Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide value-added services and leverage expertise, data-driven insights, and execution.

Role:
The Lead Data Engineer, Cyber Analytics will be a key contributor in helping Mastercard develop and deliver actionable insights and products to mitigate cyber vulnerabilities across the Mastercard ecosystem. Specifically the incumbent will:
• Design, develop, test, deploy, maintain, and improve data storage, pipelines, and ETL processes.
• Take a leadership role in collaborating with data scientists to understand existing ML and AI applications and identify optimization opportunities.
• Oversee the integration and management of data from various sources and storage systems, establishing processes and pipelines to produce cohesive datasets for analysis and modeling. opportunities.
• Partner with software engineering teams to deploy and validate production artifacts.

All About You
The Lead Data Engineer, Cyber Analytics will be a key player in helping Mastercard extract value from existing data sources to better detect, understand and prevent cyber vulnerabilities, data breaches, and subsequent fraud.
• You are fundamentally a problem-solver. You like to get into a space and understand the issues. You’re comfortable proposing solutions and working within a cross-functional team to implement that solution. You’re creative, tenacious, and kind.
• You have expertise in data – data storage, pipelines, ETL – and are always seeking to learn more. Plus you love sharing that expertise with others, helping the whole team improve.
• You are simultaneously confident and humble, able to work independently but aware that you don’t know everything and comfortable asking for help when it’s needed. You can communicate effectively and persuasively to both technical and non-technical audiences. You advocate for your projects and solutions, but you keep an open mind to alternative proposals.
 

Technical Skills
• Work history in data engineering, with a focus on building data pipelines and infrastructure for ML and AI applications. Must understand ML and AI concepts, algorithms, and techniques well enough to work in tandem with data scientists in crafting cohesive solutions.
• Familiarity with cloud (preference for AWS) and on-prem distributions.

• Strong computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis.

• Extensive experience with Spark processing engine, relational databases, and big data tools (Hive, Impala, OOZIE, Airflow, NIFI, Kafka). Basic Shell scripting and knowledge of Linux/Unix systems
• As a plus, any background with web scraping techniques and/or graphical databases.

Business Skills
• Subject matter expertise in payments, cyber, and/or fraud or proven ability to learn and master new subject matter areas.
• Creativity and Innovation. Ability to think outside the box and constantly strive for more accurate and efficient ways to perform tasks.
• Strong organizational skills and motivation, with a track record of working independently on expansive goals.
• Strong communication and collaboration. Ability to clearly articulate results of analyses, in writing and verbally, and to work effectively with all levels within the organization.

Education and Work Experience
• Higher-education degree, where you can demonstrate background knowledge of data, coding, and/or cyber (e.g., Mathematics, Statistics, Physics, Engineering, Cybersecurity, Computer Science) or work experience in which you acquired this background knowledge. Work experience required.

Mastercard is an 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. 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.