Top Hybrid Data Engineer Jobs in New York City, NY
Create machine learning models to drive value for users, advertisers, and the company. Evaluate technical tradeoffs, perform code reviews, and ensure code quality. Build scalable products iteratively without compromising quality.
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, building scalable products, and iterating quickly without compromising quality.
The Principal Machine Learning Engineer will design and implement machine learning components, build a large-scale training framework, optimize model performance with GPUs, and develop an AutoML platform. They will collaborate across teams to meet product requirements and ensure high availability and scalability.
The Senior Analytics Engineer will create data marts, work with data engineers and stakeholders for data insights, and develop high-visibility reports and dashboards. They will leverage analytical techniques to improve decision-making within the company while ensuring data quality and accessibility.
As a Senior Data Engineer, you will enhance data integration pipelines and maintain data quality within data lakes and warehouses. Collaborating with team members and stakeholders, you'll optimize data transformations and ensure the efficiency of systems. You'll also participate in code reviews and uphold coding standards while ensuring infrastructure security and data integrity.
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The Analytics Engineer will enhance the data capabilities of analysts and stakeholders by architecting data models, building data pipelines, improving data governance, and providing training. Key responsibilities include monitoring data health, developing analytic frameworks, and standardizing data processes across various domains like growth and finance.
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The Sr. Data Engineer will design and build scalable data pipelines across various sources to support data-driven decisions and generative AI initiatives. Responsibilities include collaborating with cross-functional teams, implementing data engineering principles, and optimizing performance and security of data applications.
As Director of AIDA R&D AI & Data Solutions Engineering at Pfizer, you will lead the data solutions engineering team, drive the development of innovative R&D data solutions, and oversee complex projects. You'll manage resources, ensure data security and compliance, and establish best practices in collaboration with stakeholders to optimize data storage and processing.
As a Senior Data Engineer at Hinge, you'll design and optimize data pipelines, support foundational product services, and collaborate with teams to drive data-driven decisions. You'll enhance the Data Engineering stack, advocate best practices, and maintain analytics data for insights and strategies while ensuring smooth operations through on-call participation.
The Data Manager in Risk Engineering & AI focuses on developing data-intensive solutions for decision making within the risk management function. Responsibilities include data acquisition, pipeline development, transformation, modeling, API development, collaboration with AI/ML teams, and ensuring data quality and governance.
As a Senior Data Engineer at Grubhub, you will design and maintain data pipelines, collaborate with Ads teams, optimize data storage using columnar formats, leverage technologies like Scala and Spark, and work with AWS services to ensure data integrity and efficiency while mentoring junior engineers.
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The Data Engineer will design and build scalable data systems and contribute to the architecture of Canoe's Alts Data Platform. Responsibilities include developing data models and pipelines, collaborating with AI/ML engineers, and ensuring operational excellence.
The Senior Technical Curriculum Developer will create engaging technical learning content for customers, including hands-on labs and certification programs. They will collaborate with engineering and product teams, evaluate training needs, improve existing courses, mentor junior members, and utilize SQL and scripting for reports and data handling.
Top hybrid Companies in New York City, NY Hiring Data + Analytics Roles
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