Lead Data Engineer
Mastercard (company site, opens in a new tab)PuneOn-siteDirect career pageEst. 30–48 LPA
Posted 15h ago
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Job description
Structured overview of role & requirements
About This Role
- Lead design and development of scalable batch and real-time data pipelines using Spark, Kafka, and preferably Apache Flink for Mastercard’s global data ecosystem.
- Build, optimize, and operate cloud-native data platforms on AWS, Azure, or GCP, ensuring high availability, fault tolerance, and cost efficiency.
- Provide technical leadership, mentorship, enforce best practices, and collaborate with architects and cross-functional teams to drive engineering excellence.
Minimum Requirements
- Strong hands-on experience with AWS, Azure, or GCP and cloud-native data services (S3/ADLS/GCS, EMR/Databricks, BigQuery/Redshift/Snowflake).
- Proficiency in Java (JDK 8+) with strong Object-Oriented Programming and Design skills; Python and/or Go is a plus.
- Experience building scalable data pipelines using Apache Spark, Kafka, and real-time processing frameworks (Apache Flink preferred).
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in operating at the intersection of data engineering, cloud platforms, and distributed systems at scale in a fast-paced, global environment.
- Demonstrates technical leadership with proven ability to guide engineering teams, conduct code and architecture reviews, and promote best practices.
- Strong understanding of cloud networking, security, infrastructure as code, CI/CD, and data governance frameworks, aligning with enterprise standards and compliance requirements.