Senior Staff Data Engineer - Real-Time Telemetry & Streaming

Salesforce, Inc.; United States; A distancia; USD 180.000 - 280.000; Jornada completa

Descripción de la vacante

Salesforce, Inc. is seeking a Senior Staff Data Engineer specializing in real-time telemetry to build high-velocity streaming pipelines powering internal feature platforms. You will tackle late-arriving data, stateful aggregations, and integration of diverse datasets to enable instant model reactions.

You will design ingestion pipelines, implement stream processing apps (Flink/Spark), and collaborate with ML teams to ensure feature freshness and correctness for real-time inference.

Formación

• 15+ years of data engineering experience, with a focus on high-throughput stream processing and real-time analytics.
• Strong expertise in streaming frameworks (Flink, Spark Streaming) and event brokers (Kafka, AWS Kinesis).
• Proficiency in Python, Java, or Scala; experience with real-time feature stores (Zipline, Feast).

Responsabilidades

• Design upstream event telemetry ingestion pipelines for high-fidelity data capture.
• Build and maintain real-time streaming applications to compute feature aggregations.
• Integrate diverse third-party datasets into unified streaming feature definitions.
• Resolve bottlenecks related to event ingestion into the Zipline platform.
• Define and deploy live feature contracts and monitoring for online features.
• Collaborate with ML engineers to align telemetry schemas with real-time inference needs.

Conocimientos

Apache Flink

Apache Spark Streaming

Apache Kafka

AWS

Python/Java/Scala

Herramientas

Zipline

Feast

AWS

Descripción del empleo

Salesforce, Inc. is seeking a Senior Staff Data Engineer specializing in real-time telemetry to build high-velocity streaming pipelines powering internal feature platforms. You will tackle late-arriving data, stateful aggregations, and integration of diverse datasets to enable instant model reactions.

You will design ingestion pipelines, implement stream processing apps (Flink/Spark), and collaborate with ML teams to ensure feature freshness and correctness for real-time inference.