Data Engineer II
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Before you apply
LocationPune, India
Typefull-time
SeniorityMid
Company size10,000+ people
PostedNov 3, 2026 · 5d ago
Verified live5d ago
Reposted once in the last 6 monthsEarliest listing first seen Oct 16, 2026
How we check a job is still liveAt a glanceSummarised by Seekless from the posting.
Experience working with Databricks and/or Cloudera platforms
Skilled in Spark framework (Scala/Python), Apache Kafka, Spark Streaming
Highly skilled in SQL knowledge and relational databases
Experience developing and maintaining data pipelines for extraction, transformation, and/or loading of large-scale data
Experience with large data sets and parallel processing
Strong analytics skills working with unstructured datasets
Experience performing root cause analysis on data and processes
Experience with database administration and query optimization
Experience with at least one programming language like Python
Ability to communicate requirements and solutions to diverse audiences
Familiarity with core requirements of data analysis and/or presentation
Self-sufficient problem solver with ability to deep-dive into issues
Prior experience with AWS; S3, EMR, Ozone, Iceberg
Prior experience with Python, Javascript, PLSQL, regex
Prior experience with Jenkins, Datadog, Splunk, Dynatrace
Abide by Mastercard's security policies and practices
Ensure confidentiality and integrity of information
Report any suspected information security violation or breach
Complete periodic mandatory security trainings
Skills
Databricks
Cloudera
Iceberg
Delta tables
SQL
Spark
Scala
Python
Apache Kafka
Trino
Spark Streaming
AWS
S3
EMR
Ozone
Javascript
PLSQL
regex
Jenkins
Datadog
Splunk
Dynatrace
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
Overview
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.
Responsibilities
Key responsibilities include:
• Build and maintain database technologies, environments, and applications, seeking opportunities for improvements and efficiencies
• Should be familiar and have experience in cloud data platforms like Databricks and/or Cloudera, Iceberg/Delta tables
• Writes SQL statement procedures to optimize SQL execution and query development
• Effectively utilizes various technology like Spark (Scala, Python), Apache Kafka, Trino
• Manages the deployment of data solutions that are optimally standardized and database updates to meet project deliverables
• Leads database security posture, which includes proactively identifying security risks and implementing both risk mitigation plans and control functions
• Supports process improvement efforts to identify and test opportunities for automation and/or reduction in time to deployment
• 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.
Requirements
All About You:
Should have experience working with Databricks and/or Cloudera platforms
Skilled in Spark framework (Scala/Python), Apache Kafka, Spark Streaming
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; S3, EMR, Ozone, Iceberg
• Python, Javascript, PLSQL, regex
• Jenkins, Datadog, Splunk, Dynatrace
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.