Director of Data Engineering

Join Mastercard as the Director of Data Engineering for Cyber Analytics. In this role, you will design, develop, and maintain data storage, pipelines, and ETL processes. You will lead the integration and management of data from various sources and partner with software engineering, IT, Info Sec, and infrastructure teams. You will also lead and develop a team of highly skilled data engineers.

Exposure to agentic AI

Responsibilities

• Design, develop, test, deploy, maintain, and improve data storage, pipelines, and ETL processes.
• Lead the design and build of graph database solutions and data models that support cyber analytics use cases.
• Oversee the integration and management of data from various sources and storage systems to produce cohesive datasets for analysis and modeling.
• Skilled at delegating, organizing, and motivating a team, and at prioritizing competing requests across multi-person projects
• Strong data engineering skills, including building data pipelines and infrastructure for ML and AI applications, with a solid understanding of ML and AI concepts to build solutions together with data scientists

Requirements

• Curiosity and adaptability, with the ability to learn new domains quickly and stay open to alternative ideas

Proficiency in graph databases and graph modeling techniques

• Strong computer science fundamentals in object-oriented design, data structures, algorithm design, and complexity analysis
• Skilled in databases and big data tools such as Hive, Impala, OOZIE, Airflow, and NIFI, with working knowledge of Shell scripting and Linux/Unix systems
• Clear, persuasive communication with both technical and non-technical audiences, in writing and verbally
• Strong problem-solving skills, with the ability to break down ambiguous problems, propose solutions, and implement them with cross-functional teams
• Strong stakeholder management, with the ability to build trusted relationships across technical and business partners
• Proficiency in Databricks, Spark, and AWS, with working knowledge of on-prem distributions (Apache, Hadoop, Oracle)
• Proven ability to lead and develop a team of data engineers
• A degree in a technical field such as Mathematics, Statistics, Physics, Engineering, Cybersecurity, or Computer Science, or equivalent skills gained through hands-on work
• Knowledge of the payments, cyber, and/or fraud domains

Preferred

• Knowledge of web crawling and scraping