
Description
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 Role description:The Data Engineer II will participate on data management aspects of client engagements to deliver Test & Learn and other D&S delivery solutions, as well as contribute to and foster a high-performance collaborative workplace. A Data Engineer II will:
- Independently execute projects through design, implementation, automation, and maintenance of large-scale enterprise ETL processes for a global client base
- Develop repeatable and scalable code that processes client data in an automated and efficient manner to ensure data availability in the platform is as real-time as possible.
- Act as an expert data resource within the team
- Manage the process of data delivery on teams by overseeing other Data Engineers and Analysts to deliver on-time, accurate, high-value, robust data solutions across multiple clients, solutions, and industry sectors
- Build trust-based working relationships with peers and clients across local and global teams
- Implement best practices and collaborate in the design of effective streamlined processes for a complex global solutions group
- Leverage industry best practices including proper use of source control, code reviews, data validation and testing
- Enhance big data pipelines using Python, R, SSIS and Powershell to address complex technical challenges and seamless communication with several cloud storage technologies
- Leverage new SQL Server features such as Columnstore Indexes, In-Memory OLTP, Incremental statistics, Trace Flags, SQL CLR functions, window aggregate functions, and parallel computing algorithms to reduce the processing time of multi-billion row data sets
- Contribute to the automation capabilities of the team. Implement techniques to optimize and routinize repeatable tasks for Test & Learn data setup
- Comply with and uphold all Mastercard internal policies and external regulations
Minimum job requirements:
- Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Econometrics, Engineering, Mathematics, Operations Research). Master's degree preferred
- Excellent English quantitative, technical, and communication (oral/written) skills; is an excellent listener
- Expertise and hands-on experience with RDBMS technologies, preferably with Microsoft SQL Server, the SSIS Stack and .Net
- Proficiency with at least one scripting language (Powershell, Python)
- Proven self-motivated leader with experience working in multiple teams spread across several geographies
- Demonstrated excellent skills in the ability to innovate, think critically and disaggregate problems. Able to provide oversight, validation and quality control to own and team work product
- Skilled at balancing multiple projects and differing project priorities
- Flexible to work with global offices across several time zones
Years of relevant experience:
2 - 4 years
Fields of educational study:
Computer Science, Statistics, Econometrics, Engineering, Mathematics, Operations Research
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.
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