Dremio is the pioneer of The Agentic Lakehouse—the only data platform built for agents, managed by agents. Organizations need to transform ideas into actions at unprecedented speed—Dremio delivers this agility by equipping AI agents with federated data access, unstructured data processing, and rich business context through its AI Semantic Layer. In the agentic-era, data engineering teams can’t manually tune performance for thousands of users and agents asking unpredictable questions every second. Dremio’s Agentic Lakehouse autonomously manages itself, removing undifferentiated management tasks, allowing engineers to focus on initiatives that drive business results. Dremio’s agentic lakehouse automatically optimizes queries, reorganizes data, and maintains performance at any scale. Dremio is trusted by thousands of global enterprises including Shell, TD Bank, and Michelin, and built on open standards. Dremio co-created Apache Polaris and Apache Arrow, and it's the only lakehouse built natively on Apache Iceberg, Polaris, and Arrow. Learn more at www.dremio.com.
Rating Reviews
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Pros: The technical challenges are substantial and genuinely interesting, especially for anyone passionate about data infrastructure and distributed systems. The team I work with is top-notch, very supportive, and highly skilled. The company culture encourages learning and innovation. Remote work flexibility has been a significant plus.
Cons: While the culture is collaborative, cross-team communication could be smoother to avoid duplicated efforts. Sometimes, the rapid pace of feature development means documentation or initial onboarding for new tools can lag slightly. Expect a fast-paced environment that requires quick adaptation.
Advice to Management: Continue investing in tools that streamline cross-functional communication and knowledge sharing. Empowering teams with clearer roadmaps and support for robust documentation will enhance efficiency and employee experience further.
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Pros: Dremio offers a dynamic environment for tech professionals. The company's focus on data lakehouse technology is forward-thinking, and the projects are genuinely interesting. I've had opportunities to learn new technologies and take on more responsibility. The remote work setup is well-supported, and colleagues are collaborative and smart. Leadership is generally accessible and open to feedback.
Cons: While career growth is good, sometimes the path could be more clearly defined, especially for more specialized roles. The pay and benefits are competitive for the industry, but could perhaps be reviewed more frequently against market changes. Occasional communication gaps can arise between different departments, which is typical in fast-growing tech companies.
Advice to Management: Continue fostering transparency and clear career pathing. Regularly review compensation against market rates to ensure competitiveness for all roles. Keep up the great work on company culture!
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Pros: The engineering team in Porto is fantastic – very collaborative and supportive. I learned a lot about distributed systems and data processing, which is great for career growth in the data analytics field. The hybrid work setup offers good flexibility, and most days feel productive. Management is generally accessible, and it's easy to get help when needed.
Cons: While the core technology is exciting, there can be a bit of a learning curve with some internal processes, especially around release cycles. Sometimes communication between different engineering hubs could be smoother, leading to minor delays. Compensation is competitive but perhaps not the absolute top tier in the tech industry.
Advice to Management: Continue investing in cross-team communication tools and processes to streamline collaboration between global engineering sites. Recognize and reward contributions consistently.
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What is the typical starting pay for a Data Engineer at Dremio, considering it's a growing tech company?
Based on industry trends for data roles in tech, entry-level Data Engineers at companies like Dremio in the Bay Area often see starting salaries in the range of $100,000 to $130,000 annually.
How does Dremio help category managers in the retail industry gain faster access to sales data for better decision-making?
As a category manager in retail, Dremio significantly speeds up our data access. I can query our large datasets directly without complex ETL, allowing me to analyze sales trends and optimize product assortments much quicker than before.
What's it like working in a fast-growing tech company like Dremio in the data analytics space?
It's dynamic and challenging, offering exposure to cutting-edge data lake technologies. As a data engineer in their mid-sized company, I've seen significant professional growth here.
What's it like working in a fast-growing data analytics company like Dremio?
At Dremio, a rapidly expanding data lakehouse platform company, I've found the environment to be dynamic, offering exciting opportunities for software engineers and data scientists in the tech industry.
What's it like using Dremio for category management in a mid-sized retail company?
Working with Dremio at my retail company has streamlined our category management by making data accessible for faster insights, improving our decision-making.
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