Streaming Data Platform Engineer

**Streaming Data Platform Engineer** **W2 Contract** **Pay Rate:** $55 - $65 per hour **Location:** Cupertino, CA - Remote Role **Job Summary:** We are seeking an experienced software engineer to help design and build large-scale, cloud-native data platform capabilities with a strong emphasis on real-time streaming. This is a platform engineering role, not a conventional ETL or analytics development position. The engineer will create reusable services, SDKs, frameworks, and self-service capabilities that enable internal consumers - including machine learning practitioners - to process, manage, and access high-volume data reliably. **Duties and Responsibilities:** * Design, build, and operate distributed streaming systems using Apache Flink and/or Apache Spark Structured Streaming for high-throughput, low-latency workloads. * Develop production-grade platform services, APIs, reusable frameworks, and SDKs using Python and/or Java (Spring Boot). * Contribute to control-plane and data-plane architecture, including workload orchestration, configuration, lifecycle management, and operational reliability. * Enable scalable data management for ML consumers: dataset organization, efficient access and retrieval, indexing patterns, and repeatable training-data workflows. * Engineer observability, fault tolerance, checkpointing, recovery, scaling, performance optimization, and automated testing for distributed processing systems. * Partner with platform teams, application engineers, and ML practitioners to translate use cases into self-service capabilities and well-supported developer interfaces. * Apply security and governance practices, including authentication, authorization, data protection, and appropriate handling of sensitive datasets. **Requirements and Qualifications:** * Strong hands-on real-time streaming experience with Apache Flink or Apache Spark Structured Streaming in production; able to explain design tradeoffs and incidents. * Deep understanding of distributed data processing, partitioning, state management, event-time processing, backpressure, and failure recovery. * Strong software engineering proficiency in Python or Java, including API/service design, automated tests, and maintainable code. * Experience building data platform capabilities, internal developer platforms, reusable libraries/SDKs, or large-scale backend systems - beyond individual pipelines. * Experience with microservices, containers, cloud-native deployment, CI/CD, monitoring, and production operations. * Ability to work across requirements ambiguity, evaluate architecture options, and communicate tradeoffs with engineering stakeholders. * Hands-on knowledge of both Flink and Spark, plus Databricks or comparable managed distributed-data platforms. * Experience with Java/Spring Boot and Python in the same platform ecosystem. * Experience supporting ML practitioners through training-data access, feature/dataset management, data quality, indexing, or governed data interfaces. * Familiarity with Kafka or comparable event-streaming infrastructure; schema evolution and exactly-once/at-least-once delivery tradeoffs. * Experience with Kubernetes, service orchestration, cloud object storage, data access governance, and RBAC/ABAC patterns. Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate. Bayside Solutions, Inc. may collect your personal information during the position application process. Please reference Bayside Solutions, Inc.'s CCPA Privacy Policy at