Top Senior Level Data Engineer Jobs in NYC

Build data pipelines for reliable and high-quality analytics data products, collaborate with team on design and testing, analyze technical debt and optimize design, work with Platform/Digital and DevOps team on platform requirements and security.

Join Garner as a Staff Data Engineer and drive the implementation of data pipelines for delivering core insights. Collaborate with data scientists and support pipelines in production. Mentor junior and mid-level engineers. Ideal qualifications include 7+ years of experience in building data pipelines, expertise in Python, and experience with database warehouses like Snowflake.

The MDGO Data Governance Technical Data Steward will support enterprise data management tools and integration projects, collaborate with various teams, and provide technical expertise in data governance practices.

Lead the optimization and operation of Large Language Models (LLM) aided AI products, collaborate with cross-functional teams to develop scalable LLM-based products and reusable back-end APIs, ensure APIs are scalable and performance-efficient, and foster a culture of collaboration and efficiency.

Lead the Global Procurement Data & Analytics organization, define data strategies, drive efficiencies through AI, manage D&A activities for Digital Transformation, support continuous improvement projects, and drive automation using AI.

Individual contributor position as a Data Scientist at Capital One's Emerging ML team. Responsibilities include building machine learning models, partnering with business teams, and writing software to analyze data. Ideal candidate is curious, technical, and statistically-minded.

Snap Inc is looking for a Machine Learning Engineer with 5+ years of experience to create models that drive value for users, advertisers, and the company. Responsibilities include evaluating technical tradeoffs, performing code reviews, and building robust products. The ideal candidate should have a strong understanding of machine learning approaches and algorithms, prioritize duties, and collaborate effectively.