Job Opportunities API

Strength in Trust  OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society.   The Challenge We are looking for a Principal-level, US-based, customer-facing engineer who is deeply hands-on with large-scale, distributed data systems and passionate about solving complex customer problems. You will be the technical front line for our largest enterprise customers: diagnosing and resolving production issues, shaping solutions that unlock value from our platform, and translating real-world pain points into product and engineering priorities.  This is a high-impact, visible role that reports to the SVP of engineering and partners closely with Product Management, Support, Engineering, and Customer Success. Clear, crisp communication and strong customer empathy are essential.  You Will Act as the primary technical point of contact for a portfolio of strategic enterprise customers using our big-data and high-scale services. Diagnose and troubleshoot complex issues across distributed systems, data pipelines, APIs, and integrations, often in live or near-live production contexts. Reproduce, triage, and drive resolution of incidents in partnership with Product Engineering, SRE/CloudOps, and Support. Lead deep-dive technical sessions with customers to understand their architectures, data flows, performance constraints, and success metrics. Translate customer pain points into clear problem statements, technical requirements, and prioritized backlog items for Product Management and Engineering. Guide customers through best practices for scalability, reliability, cost efficiency, and observability when using our platform. Mentor Support and Customer Success teams on technical topics so they can handle a broader range of issues independently. Create high-quality technical assets: runbooks, knowledge base articles, reference architectures, sample code, and internal playbooks. Participate in incident postmortems and drive improvements to product, tooling, and processes that reduce recurrence. Provide structured, data-driven feedback to Product Management on roadmap, usability, and technical gaps surfaced through customer engagements.  You Experience Includes 12+ years of hands-on engineering experience, with at least 3 years in a customer-facing role (e.g., Solutions Engineer, Customer/Field Engineer, Technical Account Manager, or similar)  Distributed datastores or warehouses (e.g., Cosmos DB, BigQuery, Snowflake, Databricks, Cassandra, MongoDB, similar) Large-scale data processing frameworks (e.g., Spark, Flink, Kafka, streaming pipelines) High-throughput, low-latency APIs and services in a cloud environment Proven track record of troubleshooting complex production issues across multiple layers (application, data, infrastructure, network) Hands-on experience with at least one major cloud provider (Azure, AWS, or GCP), including monitoring, logging, and observability tooling Strong scripting or programming skills (e.g., Python, Java, C#, or similar), sufficient to analyze logs, build small tools, and understand production code paths Ability to explain complex technical c