Data Engineer

Data Engineer II to contribute to the data management aspects of client engagements for Test & Learn and other Services products. In this role, you will develop robust data pipelines, implement scalable data solutions, and collaborate with cross-functional teams. Engineers work in small, flexible teams. Every team member contributes to designing, building, and testing features.
The Test & Learn team aims to build industry-leading business experimentation software that brings sophisticated analytic techniques to business users around the world. We are rapidly expanding our product offerings and innovating on how we deliver Test & Learn solutions to our clients.
Role:

• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.
• Assist in the data delivery process, working alongside Data Engineers and Analysts to support on-time, accurate, high-value, and robust data solutions across multiple clients and industry sectors.
• Use SQL and other database technologies to optimize data processing. Develop scalable and efficient code to reduce the time required to handle large data sets.
• Partner with analytics and business stakeholders to understand business questions and translate them into data requirements.
• Learn and apply industry best practices, such as version control, code reviews, and data validation, to ensure quality in data processes.
• Participate in efforts to design streamlined processes to automate routine data tasks.
• Build trust-based working relationships with peers and clients across local and global teams. Collaborate with senior and peer engineers on multiple projects in parallel.
• Comply with all Mastercard internal policies and adhere to external regulations.

All About You:

• Experience as a Data Engineer or in a similar role, with a strong understanding of data engineering concepts and methodologies, including data modeling and database design to support scalable data solutions.
• Strong knowledge of writing and optimizing SQL queries to retrieve, manipulate, and analyze data efficiently.
• Experience with Microsoft SQL Server and relational databases.
• Ability to design, implement, and maintain ETL pipelines.
• Experience with Databricks and Spark
• Experience with productivity tools such as GitHub Copilot
• Ability to innovate, think critically, and break down problems.
• Ability to handle tasks on multiple projects and navigate competing priorities.
• Ability to analyze and troubleshoot data issues and provide solutions with minimal supervision.
• Basic knowledge of testing and validating data to ensure accuracy and consistency in data pipelines.
• Excellent verbal and written communication skills, with the ability to articulate complex ideas clearly and concisely to both technical and non-technical stakeholders.
• Bachelor's degree in a quantitative discipline such as Engineering, Mathematics, Finance, Business, or a related field. Equivalent practical experience may also be considered