Top Tech Jobs & Startup Jobs in NYC, NY

Leads and develops a Data Platform engineering team while owning delivery of complex data initiatives. The role establishes delivery discipline, assesses technical and implementation risks, partners cross-functionally, and drives production reliability, data quality, observability, incident management, and on-call readiness. It also guides the evolution of scalable data ingestion, transformation, lakehouse, cloud architecture, governance, and reusable platform capabilities.

Consult PaaS clients on prior authorization decision automation programs, translating requirements into technical blueprints and partnering with Product, Design, Development, and Engineering. Build strategic improvement roadmaps, analyze healthcare authorization data, maintain dashboards and reports, monitor client KPIs, and ensure automation success throughout the customer lifecycle. The role also identifies scalable workflow improvements and guides customers in maximizing platform value.

Leads a 20-plus-person distributed Review Engineering organization across three agile squads. Owns technical direction, production reliability, incident response, system scalability, delivery metrics, hiring, performance management, and engineering career growth. Partners with Product, Design, Security, Clinical Operations, and peer engineering teams to deliver reliable, secure, high-quality systems in a regulated healthcare environment.

Designs and delivers large-scale, governed data pipelines and infrastructure across the full data lifecycle. Responsibilities include coding in Python and SQL, optimizing Airflow, dbt, AWS, Kafka, and Iceberg/Parquet workflows, implementing data quality and observability, contributing to architecture and tool evaluations, mentoring engineers, collaborating with stakeholders, and participating in on-call support.

Analyze administrative and clinical healthcare data to build reporting solutions, identify optimization opportunities, and support clinical program effectiveness. Apply statistical analysis, data mining, and predictive modeling to improve decision-making, patient outcomes, utilization, and cost efficiency. Develop dashboards and KPIs, monitor healthcare trends, collaborate with clinical, data science, engineering, and client teams, and lead complex multidisciplinary projects.

Build and independently deliver full-stack healthcare software features using Java or Groovy, React and TypeScript, MongoDB, and Kafka. Responsibilities include design, implementation, testing, deployment, production debugging, code reviews, design documentation, dependency coordination, process improvements, and mentoring. The role requires reliable delivery with minimal oversight and collaboration across engineering, product, and QA teams in a remote-first environment.

Lead end-to-end technical integrations with enterprise healthcare customers from pre-sales through production. Scope and deliver architecture, POCs, API integrations, data mappings, and runbooks. Ensure AI/ML features meet regulatory and clinical safety standards, build reusable integration patterns, collaborate cross-functionally, and mentor junior engineers to drive successful go-lives.

Investigate, triage, prioritize, diagnose, and resolve technical issues and product bugs for healthcare technology clients. Document findings, communicate priorities, provide status updates, coordinate with product and technical teams on critical issues, translate client needs into technical actions, monitor trends, and improve bug-management processes while delivering empathetic customer support.

Lead technical analysis and design of healthcare interoperability solutions, defining data exchanges and integration workflows (APIs, HL7, X12, SFTP). Conduct client discovery, produce mappings and interface specs, investigate failures, develop tests, manage multiple implementations, support launches and steady-state operations, and mentor junior analysts.

Lead client-facing engagements to design, implement, and optimize prior-authorization decision automation for PaaS customers. Translate client needs into technical blueprints, collaborate with product and engineering, build dashboards and analyze authorization data, track KPIs, and drive continuous improvement and scale across the customer lifecycle.