Senior Engineering Manager, Platform

Cobalt Streamworks is the data collaboration platform trusted for healthcare. Guided by our mission to make the world’s health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient’s request for their medical records to powering the AI revolution in healthcare, Cobalt Streamworks ers are building the future of how data is connected and used to improve health. By joining Cobalt Streamworks today, you’re stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare. We are seeking a Senior Manager to lead our Clinical Data Platform organization, responsible for building and operating the systems that power our Clinical Data Repository (CDR), Patient Data Layer (PDL), and broader clinical data initiatives. This is a technical leadership role for a hands-on, deeply experienced engineering leader who can operate across software engineering, data/ML engineering, and cloud infrastructure. You will define and drive the architecture, execution strategy, and operational excellence of a multi-tenant, multi-cloud clinical data platform that processes and serves highly sensitive healthcare data at scale. You will lead a team of high-performing engineers and technical leads, bringing clarity to ambiguity, rigor to execution, and discipline to prioritization. Success in this role requires the ability to balance long-term platform vision with near-term delivery, while maintaining high standards for reliability, security, and scalability in a regulated environment. What You Will Do: Technical Strategy & Architecture Own the technical vision and roadmap for the Clinical Data Platform. Drive architecture for multi-tenant, multi-cloud data platforms, ensuring strong isolation, scalability, and compliance Make high-stakes architectural decisions across data processing, storage, serving, and interoperability layers Ensure platform capabilities support analytics, product features, and AI/ML use cases Establish durable patterns for data lifecycle management (ingestion, validation, transformation, enrichment, serving) Execution & Delivery Lead execution of complex, cross-functional initiatives with clear prioritization and measurable outcomes Translate business and product needs into well-defined engineering plans and deliverables Drive ruthless prioritization, focusing the team on highest-impact work while managing tradeoffs across speed, quality, and cost Ensure high standards for operability, reliability, and performance in production systems Oversee delivery across batch and real-time data systems Engineering Leadership Build, lead, and scale a high-performing team of engineers and technical leads Set a high bar for technical design, code quality, and system reliability Mentor and develop engineers, creating strong technical ownership and accountability Foster a culture of ownership, urgency, and continuous improvement Partner closely with Product, Data Science, Platform, and Infrastructure teams Platform & Infrastructure Excellence Drive best practices across cloud engineering (AWS preferred), infrastructure-as-code, and environment management Ensure tight integration with platform capabilities including CI/CD, observability, security, and cost management Partner with ML Platform and Data teams to enable robust ML data pipelines and feature systems Ensure systems meet security, compliance, and auditability requirements in a healthcare environment Cross-Functional Influence Act as the technical authority for clinical data systems across the organization Collaborate with stakeholders across Product, Ops, and external partners Influence company-wide decisions on data architecture, interoperability, and platform strategy Drive alignment across teams in a multi-cloud, multi-platform ecosystem Technical Experience: Strong candidates will bring experience across cloud engineering, platform infrastructure, and modern data systems, including: Cloud Engineering (AWS preferred): Experience with core services across compute (EC2, EKS/ECS, Lambda), storage (S3), data systems (RDS, DynamoDB, Redshift), networking (VPC design, private connectivity), and security (IAM, KMS). Familiarity with multi-account and multi-region architectures and multi-cloud patterns Infrastructure & Reliability: Infrastructure-as-code (Terraform or equivalent), CI/CD integration, observability (metrics, logs, tracing), and building resilient, cost-efficient production systems Data & Distributed Systems: Distributed processing (Spark or similar), data platforms (Databricks, Snowflake), orchestration (Airflow), streaming (Kafka), and modern lakehouse architectures (Delta, Iceberg) Data Modeling & Lifecycle: Strong understanding of ingestion, transformation (dbt or similar), validation, and serving patterns for analytical and operational use cases What You B