Top Tech Jobs & Startup Jobs in NYC, NY

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Develop federated data validation frameworks, optimize queries and data models, and protect user privacy and security. The role uses Python, SQL, AWS, Airflow, PostgreSQL, Iceberg, Snowflake, Spark, and other modern data-stack technologies. It is based in New York City with in-office work three days per week.

Lead technical strategy, build and maintain software systems using AI, mentor early-career engineers, collaborate across disciplines, and protect user privacy and security. The role involves working with large-scale healthcare data in an AWS and Kubernetes environment while adopting emerging technologies and engineering practices.

Build, optimize, and maintain software systems using AI; collaborate across disciplines to solve complex healthcare technology problems; and protect user privacy and security through strong engineering practices. The role works with AWS and Kubernetes in a fast-paced startup environment and involves learning new languages, frameworks, and techniques while supporting systems that analyze large-scale medical records.

Build, optimize, and maintain scalable data pipelines and reusable datasets for business intelligence, marketing, and data science. Design a federated data validation framework, optimize queries, support data modeling and governance, and protect user privacy and security. The role uses Python, SQL, AWS, Airflow, Snowflake, PostgreSQL, and other modern data-stack technologies, with a hybrid schedule requiring three days weekly in the New York City office.

Lead and grow an engineering team building AI-enabled business productivity tools. Partner with internal business units to identify opportunities, deliver web applications and APIs, own secure and reliable services, set technical direction, and improve employee efficiency through AI adoption and foundational platform enhancements.

Lead engineering teams building Garner’s core healthcare product, including data ingestion systems and AI-enhanced product experiences. Provide technical oversight, drive scalable features, mentor and hire engineers, improve quality and delivery speed, manage cross-functional risks and tradeoffs, and protect user privacy and security. The role requires hands-on engineering experience, engineering management experience, and familiarity with web applications, APIs, and AWS cloud infrastructure.

Build and govern KPIs and dashboards, partner with stakeholders on measurement, develop scalable data pipelines, run deep-dive analyses, close reporting gaps, and promote best practices in visualization and metric consistency.

Lead end-to-end analytics: own KPIs and dashboards, define measurement with stakeholders, build scalable pipelines with Data Engineering, run deep-dive analyses, close reporting gaps, and advocate best practices in visualization, documentation, and metric consistency to inform business strategy.

Design, ship, and iterate production algorithmic systems for healthcare problems (ML, optimization, heuristics, or hybrid). Frame objectives, define metrics, validate solutions, fine-tune LLM products, and monitor outcomes while collaborating with stakeholders.

Design, develop, and productionize algorithmic systems (ML, optimization, heuristics, LLMs) for healthcare decisions. Own end-to-end solutions: problem framing, objective definition, model selection, shipping, evaluation, and monitoring to improve real-world outcomes and business metrics.