Intermediate data engineer
Summary
Build and scale streaming data infrastructure processing billions of records, including data ingestion pipelines, ML inference pipelines, and general-purpose APIs using Scala/Java, cloud platforms, Spark, Kafka, Docker, and Kubernetes.
Responsibilities: Build and scale data infrastructure that powers real-time data processing of billions of records in a streaming architecture Build scalable data ingestion and machine learning inference pipelines Build general-purpose APIs to deliver data science outputs to multiple business units Scale up production systems to handle increased demand from new products, features, and users Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs Automate and handle the life-cycle of the systems and platforms that process our data #J-18808-Ljbffr