Senior Data Engineer

Job 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**



Senior Data Engineer



Mastercard strives to be the trusted network for empowering small businesses to grow and thrive through compelling products and solutions accessible from our B2B customers and partners.

This segment is central to Mastercard's growth strategy - not only because of the impact Small & Medium Enterprises have on local, regional, and global economies but also because of their significant role in the payment ecosystem as buyers and sellers.



SME Engineering's organizational goal is to build innovative solutions and products that enable Mastercard to provide competitive solutions to small and medium businesses.



We believe in lean teams delivering a lot of value, so you will be part of a lean team potentially driving impact for the platform buildout from scratch.

The team will be addressing complex technical problems.

It will work on the latest technology like Azure/AWS cloud-native services, GraphQL, High throughput SQL/key-value/document stores, Cloud-based services, and exposure to other Mastercard tech stacks as part of the development process.



Be part of Mastercard and embrace the Mastercard Way of - Create Value, Grow Together and Move Fast by doing the right thing, focused on Decency, Inclusion, and Force for Good.



Role:

As a Senior Data Engineer, you will:

• Write high-quality, performant, clean, and testable code that adheres to best practices and coding standards, ensuring maintainability and scalability.

• Design, develop, and maintain data pipelines that automate tasks within data science and data engineering, enhancing workflow efficiency.

• Work in cross-functional teams and across different business units to tackle complex problems, fostering a collaborative and innovative environment.

• Assist in deploying and validating production artifacts, ensuring seamless integration and functionality.

• Identify opportunities to simplify and automate tasks, building reusable components that serve multiple use cases and teams.

• Create data assets that are well-modeled, thoroughly documented, and easy to understand and maintain, contributing to a robust data infrastructure.

• Develop functional requirements in complex environments, ensuring solutions meet business needs and technical specifications.

• Utilize advanced big data platforms and technologies to handle data at petabyte scale, pushing the boundaries of what is possible in data engineering.

• Build, optimize and maintain ETL pipelines using Hadoop ecosystem tools (HDFS, Hive, Spark).

• Collaborate with teams to ensure efficient and reliable data processing.

• Perform data modeling, quality checks, and system performance tuning.

• Contribute to modernization efforts, including potential cloud or Databricks integration.



All About You:

• Essential Skills to be successful:

• Proven experience in Python, PySpark and SQL, showcasing the ability to write clean, readable, and maintainable code.

• Hands-on knowledge of any big data engine, with a preference for Spark, demonstrating proficiency in managing large-scale data.

• Strong experience with CI/CD tools such as Git and Jenkins, ensuring efficient and reliable code deployment.

• Excellent communication skills, enabling effective collaboration and knowledge sharing.

• Highly skilled in problem-solving, capable of addressing complex challenges with innovative solutions.

• Exhibits a high degree of initiative and a strong curiosity, with a desire to continuously learn and grow.

• Strong understanding of Agile methodologies, with the ability to drive iterative delivery and cross-team collaboration.

• Strong communicator with the ability to explain complex concepts to both technical and non-technical audiences, and to influence stakeholders across product, engineering, and acquisition teams.

• Bachelor’s degree in Computer Science, Data Analytics, Mathematics, Software Engineering, or a related field or equivalent practical experience.

• Programming language: Java/Scala/Python

• Data processing framework: Spark

• BigData Hadoop Frameworks: Hive, impala, oozie, airflow, Hdfs

• Any cloud provider experience.

Services like S3, Athena, EMR, Redshift, Glue, Lambda etc..

• Data & AI platform: Databricks



Nice to have:

• Experience in with data engineering on petabyte scale data

• Passion of Machine Learning

• Comfortable with pioneering new technology



**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.

Required Skill Profession

Other General