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Job Description
Structured overview of role & requirementsAbout This Role
Own design, development, and maintenance of scalable batch and real-time data pipelines using technologies like Maxwell, Kafka, Spark, and dbt to support analytics and business-critical applications.
Build and optimize cloud-native data platforms (S3, Spark, Trino, BigQuery) and data models following Medallion Architecture to create reliable, reusable datasets for Product, Analytics, and Business teams.
Ensure end-to-end pipeline lifecycle management including high availability, monitoring, SLA adherence, data quality, security, and automation to improve platform reliability and developer experience.
Minimum Requirements
Minimum 4+ years of hands-on experience in designing and building scalable data platforms, data lakes, and data warehouses.
Strong proficiency in Spark (Scala, Python) and SQL with production-grade data pipeline experience and distributed data processing knowledge.
Experience with batch and streaming pipelines using Kafka, CDC/Maxwell or similar event-driven architectures.
Experience with cloud-native data platforms such as Amazon S3, BigQuery, Trino, and hands-on dbt development including testing and documentation.
Ideal Candidate Profile
Experienced with modern data lake architectures and dimensional data modeling (Medallion Architecture, star schemas) supporting analytics and BI.
Skillful in optimizing large-scale Spark jobs, SQL queries, and distributed processing for performance, scalability, and cost efficiency.
Able to independently design, build, and manage critical data infrastructure while collaborating cross-functionally with Product, Engineering, Analytics, and Business stakeholders.