Senior Data Engineer

Mastercard; Maharashtra; Sur place; INR 2 200 000 - 3 800 000; Plein temps

Résumé du poste

Mastercard in India is seeking a Senior Data Engineer / MLE to design and build scalable data pipelines and ML-ready datasets. You will partner with platform engineering, data science, and BI stakeholders to deliver reliable data products that power analytics across the business.

The role emphasizes strong SQL/Python, Spark-based pipelines, and cloud data ecosystems (AWS). You will ensure data quality, governance, and robust CI/CD practices, while communicating effectively with cross-functional

Qualifications

• Strong proficiency in SQL and Python (or Scala) for data engineering.
• Experience building data pipelines with Spark, PySpark, Hadoop.
• Experience with AWS, S3, and Databricks.
• Knowledge of data modeling and data quality concepts.
• Experience with cloud data ecosystems and object storage.
• Ability to troubleshoot production pipeline performance.
• Strong communication and cross-team collaboration.

Responsabilités

• Design, build, and maintain scalable data pipelines.
• Develop curated datasets and data models for analytics and ML.
• Implement pipeline reliability patterns (monitoring, retries, CI/CD where applicable).
• Collaborate with data scientists to enable feature engineering and model deployment.
• Ensure secure data handling per governance and compliance.
• Drive engineering best practices (code quality, testing, documentation).

Connaissances

SQL & Python

Spark/PySpark

Databricks

Hadoop

Data modeling

AWS

Data quality

Troubleshooting

Communication

Outils

AWS

S3

Databricks

Spark

Description du poste

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.

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

Senior Data Engineer

Data Engineer / Machine Learning Engineer

Level 7 | FTE | Needed: Q3

Overview

The Data Engineering team builds trusted, scalable datasets and pipelines that power analytics, BI, and machine learning use cases across Mastercard. This role will help design and deliver resilient data pipelines, curated data models, and ML-ready feature datasets while partnering closely with platform engineering, data science, and BI stakeholders.

Role

As a Data Engineer / MLE, You Will

• Design, build, and maintain scalable batch and near-real-time data pipelines.
• Develop curated datasets and data models that enable reliable analytics and ML workloads.
• Implement pipeline reliability patterns (monitoring, alerting, retries, performance tuning).
• Partner with data scientists to enable feature engineering and model operationalization.
• Ensure secure data handling aligned to enterprise governance and compliance expectations.
• Drive engineering best practices (code quality, testing, documentation, CI/CD where applicable).

All About You

Essential Skills (Must Have):

• Strong proficiency in SQL and Python (or Scala) for data engineering.
• Experience building data pipelines using distributed processing (e.g., Spark,PySpark,HADOOP).
• Experience in using data technology technology like AWS, S3, Databricks.
• Solid understanding of data modeling (dimensional and/or lakehouse patterns) and data quality concepts.
• Experience working with cloud data ecosystems (AWS preferred) and object storage / lake patterns.
• Ability to troubleshoot performance and reliability issues in production pipelines.
• Strong communication skills and ability to collaborate across engineering and analytics stakeholders.

Nice To Have

• Experience with Databricks or similar lakehouse platforms.
• Exposure to ML feature pipelines, model deployment patterns, or MLOps concepts.
• Experience in payments / banking / regulated environments.
• Familiarity with data governance tooling (catalog, lineage) and PII handling patterns.

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.