SEND Continuum - Data WARE HOUSE
Mastercard (company site, opens in a new tab)PuneOn-siteDirect career pageEst. 12–22 LPA
Posted 12h 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 using distributed processing technologies like Spark.
- Develop curated datasets and data models that support reliable analytics and machine learning workloads, including feature engineering and model operationalization.
- Implement and maintain pipeline reliability patterns such as monitoring, alerting, retries, and performance tuning while ensuring secure data handling aligned with governance and compliance requirements.
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.
- Understanding of data modeling (dimensional and/or lakehouse patterns), data quality concepts, and cloud data ecosystems (AWS preferred).
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced with cloud-based data platforms, especially AWS, and comfortable with object storage and lake patterns.
- Capable of troubleshooting production pipeline performance and reliability issues and collaborating effectively across engineering and analytics teams.
- Familiarity with machine learning feature pipelines, MLOps practices, or regulated environments like payments/banking is a plus but not mandatory.