Senior Data Engineer
Mastercard (company site, opens in a new tab)PuneOn-siteDirect career pageEst. 25–45 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain scalable batch and near-real-time data pipelines that support analytics, BI, and ML workloads.
- Develop curated data models and ML-ready feature datasets while ensuring secure handling and compliance with enterprise governance.
- Collaborate with data scientists, platform engineers, and BI stakeholders to enable feature engineering, model operationalization, and enforce engineering best practices including monitoring and performance tuning.
Minimum Requirements
- Strong proficiency in SQL and Python (or Scala) for data engineering tasks.
- Experience building data pipelines using distributed processing frameworks such as Spark, PySpark, or Hadoop.
- Familiarity with cloud data technologies, particularly AWS, S3, and Databricks or similar lakehouse platforms.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Technical proficiency with cloud data ecosystems and distributed data processing at scale, particularly AWS and Spark/PySpark.
- Experience in building reliable and secure data pipelines with attention to performance tuning and pipeline reliability.
- Ability to collaborate effectively with cross-functional teams including data science and BI to support ML and analytics use cases in regulated or payment-related environments.