📍
Pune, India

Data Engineer II

No experience
Finance
Data / Analytics
Posted:
December 29, 2025

Mastercard

Worldwide payments technology and solutions provider
79
Palpable Score
Apply >view company >

Title and Summary

Data Engineer II

Job Description Summary

We are looking for a Data Engineer to join the Data Engineer team. This is a pivotal role, responsible for supporting multiple Data Analysts and Data Scientists day-to-day and assisting various data-driven requests across the company. The position involves a wide variety of technical skills, from coding to infrastructure, from data analysis to database management. The ideal candidate will have experience working with large-scale data and building automated data ETL processes for large-scale data analysis. ODS or data warehousing experience would be ideal.

Key responsibilities include:

Designing, implementing, and maintaining the tooling and infrastructure that enables our Analysts and Data Scientists to work efficiently and effectively.

Participating in the entire solution development cycle from requirement gathering to solution deployment.

Working with multiple stakeholders across teams to fulfill ad-hoc investigations, including large-scale data extraction, transformation, and analyses.

Supporting production code to produce comprehensive and accurate data artifacts.

Promoting strategies to improve our data modeling, quality, and architecture.

All About You:

Highly skilled in SQL knowledge and relational databases.

Experienced with developing and maintaining data pipelines for the extraction, transformation, and/or loading of large-scale data.

Experienced with working with large data sets. You’ve implemented parallel processing and have dealt with the limitations and challenges of working with terabytes of data.

Strong analytics skills related to working with unstructured datasets.

Experienced with performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.

Experienced with database administration and query optimization with different databases.

Experienced with at least one of the programming languages like Python

Capable of effectively communicating requirements and solutions to audiences with different skill sets.

Familiarity with the core requirements of data analysis and/or presentation.

Focused, innovative, and self-sufficient problem solver who is willing to independently and creatively deep-dive into an issue, cut to the heart of a problem, and solve it.

Bonus Points if:

You have any prior experience with any of the following:

• AWS; specifically Redshift, Kinesis, EMR, S3, Cloud Formation, Data Pipeline, Athena, SageMaker, Glue

• Python, PHP, Javascript, PSQL, regex, Tableau,

• Jenkins, Datadog, Splunk

About the company

Mastercard

Company overview
Mastercard operates a global payments network that routes, clears, and settles card and other payment transactions across countries and currencies. The company also sells value-added services and solutions, including security solutions, consumer acquisition and engagement services, business and market insights, digital and authentication solutions, and processing and gateway services. The company serves financial institutions, merchants, governments, fintechs, and partners with technology and data products alongside the network. Mastercard is a public company headquartered in Purchase, New York.

Locations and presence

Mastercard employed approximately 35,300 people globally as of December 31, 2024, with around 69% of employees based outside the United States across more than 90 countries. Mastercard describes a hybrid work approach for non-remote roles that averages at least three days per week in the office, alongside flexibility programs such as a four-week “work from elsewhere” policy.

Palpable Score

79
/ 100
Mastercard is a strong early-career option because Mastercard runs paid internships with a stated path into the Launch graduate program, and Mastercard also backs recent grads with an 18-month structured development journey. The main limits are predictability and consistency across teams: candidates report a wide range of interview styles depending on role, and the company’s pay transparency is strong in some markets but not universal.
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