Offices at Fluent, Inc.

Fluent, Inc. is headquartered in New York, New York, USA and has 3 office locations.

Hybrid Workplace

Employees engage in a combination of remote and on-site work.

Colleagues in the NYC metro will be required to work from the office on Tuesdays and Thursdays. In-office collaboration days will have catered lunches and host the majority of our programming. Our hybrid two-day schedule is built around flexibility.

U.S. Office Locations

Global Office Locations

HQ

New York, New York, USA

300 Vesey Street 9th Floor, New York, NY, United States

Jobs At This Office

Overland Park, Kansas, USA

5440 West 110th Street, Suite 300, Overland Park, Kansas, United States, 66211

Toronto, Ontario, CAN

200 Bay St. Tower, Suite 1200, Toronto, ON, Canada, M5J 2J2

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Fluent, Inc.

Partner Success Manager (AdTech)

3 Days Ago

New York, NY, USA

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AdTech • Digital Media • eCommerce • Marketing Tech

The Partner Success Manager will manage relationships with partners, driving campaign growth and optimizing performance through market analysis and collaboration with various teams. Responsibilities include onboarding partners, executing project strategies, reporting insights, advocating for partner needs, and managing billing and forecasts.

Fluent, Inc.

Data Engineer (Databricks)

6 Days Ago

Toronto, ON, CAN

Remote

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AdTech • Digital Media • eCommerce • Marketing Tech

As a Data Engineer at Fluent, you will build and manage data products on the Databricks platform, focusing on creating robust data pipelines and ensuring quality and integration with machine learning models. Your role will involve collaborating with various teams to understand data requirements and keep up with emerging technologies in the Databricks ecosystem.

Fluent, Inc.

Sr. Data Engineer (Databricks)

6 Days Ago

Toronto, ON, CAN

Remote

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AdTech • Digital Media • eCommerce • Marketing Tech

As a Sr. Data Engineer at Fluent, you will develop and manage scalable pipelines in the Databricks environment, focusing on high-impact data solutions. You'll work on integrating machine learning models and ensure data observability standards. Collaboration with data science and reporting teams is essential to translate requirements into effective data models.

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