PUNE · FULLTIME
Sr Data Engineer
Mastercard
Pune · onsite · Posted 64d ago
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Undisclosed4–8 yrsfulltimePune
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Section · 01
About this role
JOB DESCRIPTION Our Purpose
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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 Level 7 | FTE | Needed: Q3
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).
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 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.
All activities involving access to Mastercard assets, information, and networks come 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
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Section · 02
Skills
modelingbidata qualityApache SparkScalaPerformance Tuningamazon web servicesApache HadoopQuality conceptsDatabricksPysparkData EngineeringPythonSQLCommunication SkillsData GovernanceData ModelingData PipelineData ScienceMachine Learning
Section · Company
About MasterCard
Mastercard
FinTech
7.9k+
employees
1966
60 years old
Purchase,New York
United States
About
Payments Technology company enabling transactions
Industries
FinTechFinancial ServicesInternet
Employee ratings
1,001 reviews
3.8/ 5
Culture
3.8
Career growth
3.1
Work-life
3.8
Employees rate it well for
Work Life Balance231Work Culture142Salary110Senior Management75Job Security55
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