![]()
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
