Inviting Senior Data Engineers

About Fusemachines Fusemachines is a 10+ year old AI company, dedicated to delivering state-of-the-art AI products and solutions to a diverse range of industries.

Founded by Sameer Maskey, Ph.D., an Adjunct Associate Professor at Columbia University, our company is on a steadfast mission to democratize AI and harness the power of global AI talent from underserved communities.

With a robust presence in four countries and a dedicated team of over 400 full-time employees, we are committed to fostering AI transformation journeys for businesses worldwide.

At Fusemachines, we not only bridge the gap between AI advancement and its global impact but also strive to deliver the most advanced technology solutions to the world.

Type : Remote Full-time Inviting Senior Data Engineers Are you an experienced Data Engineering professional with a passion for building scalable, reliable, and high-performance data systems?

Do you have hands-on experience designing and optimizing end-to-end real-time and batch pipelines, and developing cloud-native data architectures using modern technologies such as AWS, GCP, Azure, Databricks, and Snowflake?

We are building a dynamic pipeline of pre-qualified talent to fill critical data engineering roles as our business continues to scale.

By providing your information, you are included in our priority pipeline of highly qualified candidates across various specialized Data Engineering opportunities within Fusemachines.

This curated list ensures you will be among the very first to receive consideration for future full-time opportunities, giving you a significant advantage and leading to a much shorter evaluation and interview process when a critical role opens.

Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

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