Data Scientist II

Posted Yesterday
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Gurugram, Haryana, IND
Hybrid
Entry level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Design and maintain scalable ETL/ELT pipelines and batch or real-time data processing solutions using SQL, Python, and Spark. Ensure data quality, reliability, monitoring, and observability across enterprise platforms. Apply version control, CI/CD, DataOps, testing, and automated deployment practices. Support platform migrations and production operations while collaborating with engineers, scientists, analysts, and business stakeholders. Participate in technical reviews, troubleshoot complex data issues, and maintain documentation and operational standards.
Summary Generated by Built In
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 Scientist II
Overview• Are you excited about Data Assets and the value they brings to an organization? • Are you an evangelist for data driven decision making?• Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across 6 continents?• Do you want to be the go-to resource for data analytics in the company?
Role• Design, develop, and maintain scalable ETL/ELT pipelines supporting enterprise data and analytics initiatives.• Build and optimize batch and real-time data processing solutions using SQL, Python, Spark, and related technologies.• Ensure data availability, accuracy, consistency, and reliability across data platforms and pipelines.• Implement data quality controls, testing frameworks, monitoring, and observability practices to support trusted data products.• Apply engineering best practices including version control, CI/CD, DataOps, and automated deployment methodologies.• Support platform upgrades, migrations, operational maintenance, and ongoing production support activities.• Collaborate with Data Engineers, Data Scientists, Analysts, and business stakeholders to translate business requirements into scalable data solutions.• Participate in technical design reviews, code reviews, and architecture discussions to drive engineering excellence.• Create and maintain technical documentation, standards, and operational procedures.
All About You• Hands-on experience in data engineering, data integration, and large-scale data processing.• Strong proficiency in SQL and Python for data transformation, automation, and analytics workloads.• Solid understanding of data modeling, database design, and performance optimization techniques.• Experience designing and developing ETL/ELT solutions across modern data platforms.• Knowledge of data quality frameworks, testing methodologies, and data validation practices.• Familiarity with cloud-based or modern enterprise data platforms.• Experience with source control, CI/CD pipelines, and software engineering best practices.• Strong analytical and problem-solving skills with the ability to troubleshoot complex data issues.• Excellent communication and collaboration skills with the ability to work effectively across technical and business teams.• Self-motivated, detail-oriented, and committed to delivering high-quality, scalable solutions.
Preferred Qualifications• Experience with PySpark and Apache Spark for distributed data processing.• Experience working within the Hadoop ecosystem and large-scale data environments.• Familiarity with GitLab, Jenkins, or similar DevOps and CI/CD platforms.• Exposure to Power BI or other business intelligence and data visualization tools.• Understanding of modern data architecture patterns supporting analytics, machine learning, and AI workloads.
Education• Bachelor's or Master's Degree in a Computer Science, Information Technology, Engineering, Mathematics, Statistics, M.S./M.B.A. preferred
Additional Competencies• Excellent English, quantitative, technical, and communication (oral/written) skills • Analytical/Problem Solving• Strong attention to detail and quality• Creativity/Innovation• Self-motivated, Self Starter, operates with a sense of urgency• Project Management/Risk Mitigation• Able to prioritize and perform multiple tasks simultaneously
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.

Skills Required

  • Hands-on experience in data engineering, data integration, and large-scale data processing
  • Strong proficiency in SQL and Python
  • Understanding of data modeling, database design, and performance optimization
  • Experience designing and developing ETL/ELT solutions across modern data platforms
  • Knowledge of data quality frameworks, testing methodologies, and data validation
  • Familiarity with cloud-based or modern enterprise data platforms
  • Experience with source control, CI/CD pipelines, and software engineering best practices
  • Strong analytical, problem-solving, communication, and collaboration skills
  • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Mathematics, or Statistics
  • Experience with PySpark and Apache Spark
  • Experience with the Hadoop ecosystem and large-scale data environments
  • Familiarity with GitLab, Jenkins, or similar DevOps and CI/CD platforms
  • Exposure to Power BI or other business intelligence and data visualization tools
  • Understanding of modern data architecture supporting analytics, machine learning, and AI workloads
  • Master of Science or Master of Business Administration degree

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support Retirement plans are presented as best-in-class with a high company match on 401(k) or local equivalents. Career materials and U.S. postings consistently highlight retirement matching as a standout feature.
  • Leave & Time Off Breadth U.S. postings describe generous paid time off including vacation, personal days, holidays, sick/safe time, and additional bereavement leave. A hybrid policy and a limited “work from elsewhere” option further support time away.
  • Parental & Family Support Company pages state a global minimum of 16 weeks of paid new-parent leave across birth, adoption, and foster, plus family-building assistance where permitted. Mental-health resources and caregiving supports are also emphasized.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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About our Teams

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Hybrid Workspace

Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

Typical time on-site: 3 days a week
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