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Mastercard

Data Engineer II

Posted 2 Days Ago
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Hybrid
Pune, Mahārāshtra
Mid level
Hybrid
Pune, Mahārāshtra
Mid level
This role involves designing and maintaining data infrastructure for Analysts and Data Scientists, supporting large-scale data ETL processes and enhancing data quality and architecture.
The summary above was generated by AI
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 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
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.

Top Skills

Athena
AWS
Cloud Formation
Data Pipeline
Datadog
Emr
Glue
JavaScript
Jenkins
Kinesis
PHP
Psql
Python
Redshift
S3
Sagemaker
Splunk
SQL
Tableau

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