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Mastercard is hiring for a FRESHER entry level Data Analyst role in India



The opening has been closed a few minutes after posting, please don't apply now.

Position:

  • Data Analyst, Big Data Insights and Engineering, focused on data unification, analytics, and building scalable data driven solutions across multiple datasets
  • Entry level role designed for individuals who want to work at the intersection of data engineering, analytics, and product innovation
  • Involves working closely with cross functional teams to translate raw data into meaningful insights that influence product development and business strategy
  • Opportunity to contribute to next generation cyber intelligence products powered by large scale data processing and advanced analytics
  • Requires strong curiosity for solving complex data problems and the ability to work with modern data ecosystems

Company:

  • Mastercard
  • A globally recognized technology company operating in the digital payments and financial services domain
  • Known for enabling secure and seamless transactions across individuals, businesses, and governments
  • Focuses on innovation in payments, cybersecurity, and data intelligence to power economies worldwide
  • Operates across more than 200 countries and territories, connecting financial ecosystems through advanced infrastructure and partnerships

Location:

  • Gurgaon, India
  • One of the major technology and financial hubs in India with a strong presence of global companies
  • Offers exposure to international projects and collaboration with global teams

Job type:

  • Full time
  • Permanent role within the organization

Job mode:

  • Onsite or Hybrid depending on team and business requirements
  • Involves collaboration with internal teams, stakeholders, and global counterparts

Job requisition id:

  • R 271905

Years of experience:

  • 0 to 3 years
  • Suitable for freshers and early career professionals looking to enter data analytics or data engineering roles

Company description:

  • Mastercard operates as a leading force in the global digital payments ecosystem, supporting financial transactions across individuals, enterprises, and governments
  • The company focuses on building an inclusive digital economy where financial access is available to everyone, regardless of geography or economic background
  • Through its advanced technology platforms, Mastercard ensures that transactions remain secure, efficient, and accessible
  • The organization invests heavily in innovation, especially in areas like cybersecurity, artificial intelligence, and data intelligence
  • Its ecosystem is powered by strong partnerships with financial institutions, merchants, fintech companies, and governments
  • Mastercard emphasizes ethical values through its internal culture, which is guided by principles of trust, integrity, and responsibility
  • The company’s global reach allows it to influence economic growth by enabling digital commerce and reducing barriers to financial participation
  • Employees benefit from working in a highly collaborative environment that values diversity, inclusion, and continuous learning
  • Mastercard is also committed to sustainability, aiming to create long term impact through responsible business practices
  • The organization encourages employees to contribute ideas that can shape future products and services, making it an ideal place for innovation driven professionals

Profile overview:

  • The Analyst role in Big Data Insights and Engineering focuses on integrating and analyzing data from multiple sources to create unified data views
  • The candidate will be responsible for building pipelines that collect, process, and transform data into structured formats for analysis
  • The role involves working with large scale datasets that are complex, high volume, and multi dimensional in nature
  • A key responsibility includes collaborating with teams such as product management, data science, and engineering to deliver impactful data solutions
  • The position requires the ability to identify patterns, trends, and anomalies within datasets and translate them into actionable insights
  • The candidate will contribute to the development of innovative data driven products, especially in cybersecurity and digital payments
  • The role also includes building prototypes and proof of concepts to validate new ideas and technologies
  • There is a strong emphasis on data driven decision making, where insights generated from analysis directly influence business outcomes
  • The candidate will work on enhancing existing data systems by integrating new data assets that improve the value proposition for customers
  • Exposure to real world data challenges will help the individual develop both technical and analytical expertise
  • The role requires adaptability, as the candidate will need to switch between technical implementation and business understanding
  • The analyst will also be expected to communicate insights effectively to both technical and non technical stakeholders
  • Overall, the position offers a blend of data engineering, analytics, and product innovation responsibilities

Qualifications:

  • Strong foundation in programming languages such as Python, with hands on experience in libraries like Pandas, Numpy, and PySpark
  • Good understanding of SQL for querying and manipulating large datasets
  • Exposure to big data technologies such as Hadoop for data storage and processing
  • Familiarity with data integration tools like Apache NiFi, Azure Data Factory, Pentaho, or Talend
  • Basic knowledge of machine learning concepts and data mining techniques
  • Understanding of data modeling, data transformation, and reporting methodologies
  • Experience or exposure to business intelligence platforms for data visualization and reporting
  • Knowledge of generative AI or large language models for automating data workflows is an added advantage
  • Ability to work with structured and unstructured data from multiple sources
  • Strong analytical thinking and problem solving skills
  • Capability to identify data inconsistencies and ensure data quality
  • Understanding of metrics, benchmarking, and performance measurement techniques
  • Familiarity with graph databases is considered beneficial but not mandatory
  • Ability to collaborate effectively with cross functional teams
  • Good communication skills to explain complex data concepts in a simple manner
  • Ability to manage multiple tasks in a fast paced environment
  • Willingness to learn new tools and technologies as required by the role

Additional info:

  • The role involves handling sensitive financial and transactional data, making information security a key responsibility
  • Employees are expected to strictly follow company policies related to data security and confidentiality
  • Any potential security risks or breaches must be reported promptly
  • Regular training sessions are conducted to ensure employees stay updated on security practices
  • The organization values integrity and expects candidates to maintain honesty throughout the hiring process
  • Candidates are encouraged to follow ethical practices during interviews and assessments
  • The company provides opportunities for continuous learning and skill development
  • Exposure to global teams allows employees to gain international work experience
  • The work environment encourages innovation, collaboration, and knowledge sharing
  • Employees get the chance to work on cutting edge technologies in data and analytics
  • The role provides a strong foundation for career growth in data science, analytics, and engineering domains
  • There is significant focus on building scalable and efficient data systems that support business operations
  • Employees are encouraged to take ownership of their work and contribute ideas that drive improvement
  • The organization promotes diversity and inclusion, ensuring equal opportunities for all employees
  • This role serves as a stepping stone for individuals aiming to build a career in the data and technology industry

The opening has been closed a few minutes after posting, please don't apply now.

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