Data Engineer II
Arlington, Virginia
Applications have closed
Mastercard
Wir verbinden und fördern eine integrative, digitale Wirtschaft, von der Menschen, Unternehmen und Regierungen weltweit profitieren, indem wir Transaktionen sicher, einfach und zugänglich machen.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
Data Engineer IIOverview:Mastercard’s Technical Implementation - Data and Delivery team part of the Mastercard’s Test and Learn team, is seeking a Data Engineer II to drive customer experience strategy through innovation and problem-solving while contributing to a collaborative, high-performance workplace. This is a hybrid position located in Arlington, VA, with three days per week onsite.
The Test & Learn team within Mastercard's Services organization 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.
Technical Implementation is a core component to these services, managing the data acquisition, integration, and transformation of client provided data within the Test & Learn and other platforms for global engagements.
Role:
• Support the design, implementation, and maintenance of enterprise ETL processes for data platforms, for a global client base.
• Develop scalable and efficient code to process data, ensuring availability and accessibility in a timely manner.
• Collaborate with senior engineers to address data challenges, contributing to solutions that maintain high data quality.
• Assist in the data delivery process, working alongside Data Engineers and Analysts to support accurate, high-value data solutions across various clients and industries.
• Build strong working relationships with team members and clients, contributing to both local and global projects.
• Learn and apply industry best practices, including version control, code reviews, and data validation, to ensure quality in data processes.
• Use SQL and other database technologies to help optimize data processing and reduce the time required to handle large data sets.
• Participate in efforts to automate routine data tasks and streamline processes.
• Comply with all Mastercard internal policies and adhere to external regulations.
All Abut You:
• Strong knowledge of writing and optimizing SQL queries to retrieve, manipulate, and analyze data efficiently.
• Experience with Relational Databases (RDBMS), with strong hands-on expertise in Microsoft SQL Server and related technologies.
• Experience with SSIS (SQL Server Integration Services) for ETL processes and data transformations.
• Familiarity with ETL frameworks and the ability to design, implement, and maintain data pipelines.
• Understanding of data modeling concepts and database design to support scalable data solutions.
• 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.
• Strong interpersonal skills to work effectively in a team environment and communicate technical concepts to non-technical stakeholders.
• Demonstrated willingness to learn new tools, technologies, and methodologies to improve skills and contribute to the team’s success.
• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Econometrics, Engineering, Mathematics). Equivalent practical experience in data engineering, data analytics, software development, or related fields will be considered.
This role is not eligible for Mastercard’s work authorization sponsorship. As such, candidates must be eligible to work in the United States, now as well as in the future, without employer sponsorship.
#LI-NF1Mastercard 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 reasonable_accommodation@mastercard.com 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Computer Science CX Data Analytics Data pipelines Data quality Econometrics Engineering ETL Mathematics Pipelines RDBMS Security SQL SSIS Statistics Testing
Perks/benefits: 401(k) matching Competitive pay Fitness / gym Flex hours Flexible spending account Flex vacation Health care Insurance Medical leave Salary bonus
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