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À propos de ce poste Senior Data Engineer-2 chez Mastercard

Mastercard · Sur site · Pune, India

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-2

Who is Mastercard?
Mastercard is a global technology company in the payments industry. Our mission is 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. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Overview
Are you an experienced data engineer with a passion for technological innovation, have a can-do attitude and strong sense of ownership? The Small and Medium Enterprise (SME) platform is the perfect opportunity for you to assist in the design & development of a world-class unified platform, enabling Small and Medium Enterprises globally.

The SME team is looking for a Senior Data Engineer to own the development of data pipelines to create a SME data mart on prem and on cloud. You will also work closely with cross-functional teams, including data scientists, data analysts, and software engineers, to drive data-driven decision making throughout the organization.

Role
• Independently design and implement data pipelines that are scalable, reliable, and reusable using various programming languages and frameworks such as SQL, PySpark, Impala etc.
• Develop and maintain efficient ETL processes to handle large volumes of data (billion level) from different sources and store in centralized storage (data warehouse and lake house).
• Collaborate with data scientists, data analysts and software engineers in scrum teams to understand their data needs and develop data solutions that enable them to access, analyze and visualize data more effectively.
• Work with data architects to ensure that data infrastructure aligns with the organization’s data architecture and governance standards. Ensure data quality, security, and compliance with industry regulations.
• Troubleshoot and resolve issues with data pipelines and integrations, ensuring they are running smoothly and efficiently. Monitor and optimize performance of data systems, proactively identifying and addressing bottlenecks and limitations.
• Maintain documentation for data pipelines, troubleshooting logs and data processing systems.
• Support the design and implementation of data models, algorithms and feature stores that serves BI reporting and machine learning models.
• Mentor and support junior data engineers, providing guidance and support as needed.
• Stay up to date with emerging technologies and trends in the data engineering space, recommend their adoption as appropriate.

All About You
• Demonstrated ability to independently design and implement data pipelines in large-scale data systems and distributed computing framework following best coding practice.
• Extensive hands-on experience with SQL and SPARK.
• Experience with big data tools / technologies. (Hadoop, NIFI, Kafka, Impala, HIVE, OOZIE, Airflow etc.)
• Knowledge of cloud-based data storage and processing systems. (Azure, AWS, GCP, databricks etc)
• Experience with data modelling (SQL and NoSQL), data ETL and data warehousing concepts.
• Experience with implementing analytical data pipeline for data science projects and experience of creating feature stores will make your application stand out.
• Excellent communication skills, with the ability to work in a team and collaborate with other data professionals and business stakeholders.
• Strong attention to details and the ability to work under tight deadlines in fast-paced environment.
• Working experience of using CI/CD to keep data pipeline scalable and reliable.
• Working experience of using common programming languages. (Python preferred)
• BSc or higher degree in computer science or relevant fields.

Nice to have:
• Databricks certifications (Data engineer professional, Hadoop migration architects)
• AWS Big Data, Data Analytics certification and / or Azure Data Engineer certification

Corporate Security Responsibility
Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and therefore, it is expected that the successful candidate for this position 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.

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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À propos de Mastercard

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.

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