Apache Spark Software Engineer Jobs

Build and operate scalable cloud infrastructure and data services across AWS and GCP as a DevOps Engineer III. You’ll automate deployments, strengthen observability and reliability, and use modern AI-powered tooling to improve infrastructure operations.

Lead customer-facing technical engagements for Databricks, designing cloud data solutions, building proofs of concept, and delivering live demos. This builder-oriented role combines architecture, coding, technical strategy, and customer relationships across data engineering, analytics, and machine learning.

Lead Roku’s machine learning strategy for its Content Platform, building scalable production models and integrating generative AI and vision capabilities. You’ll connect deep AI research with rapid product delivery that improves content discovery and engagement.

Lead the architecture and delivery of secure, production-scale generative AI and machine learning systems at Okta. You’ll build LLMOps, RAG, evaluation, agentic application, and platform capabilities while mentoring engineers and shaping the company’s GenAI strategy.

Lead enterprise data architecture engagements for Snowflake customers, combining deep data engineering expertise with executive-level communication across the sales cycle. You’ll design and demonstrate cloud data platform solutions, support proofs of concept, and help customers implement modern lakehouse and data pipeline architectures.

Build and productionize secure data and AI solutions for federal customers as a hands-on Senior Forward Deployed Engineer. You will own architecture, implement end-to-end systems, and help customers turn Databricks technology into measurable impact.

Help customers solve complex data and analytics challenges through hands-on technical evaluations, Spark programming, and solution architecture. This customer-facing role combines pre-sales consulting, cloud integration, and technical community engagement.

Build and operate DigiCert’s scalable data and ML platform, with deep ownership of Databricks infrastructure, production pipelines, governance, and reliability. Partner with data scientists and engineering teams to turn experimentation into dependable production systems.