San Francisco, California, United States of America
Company Overviews
GoodData is the AI-native, full-stack decision intelligence platform that helps businesses turn data into actionable, enterprise-grade insights. Build, operationalize, embed, and monetize trusted analytics, workflows, and AI agents at scale—fully governed, auditable, and ready to scale.
Our mission: Turn data into intelligence that’s secure and embedded wherever decisions happen. That’s why we built a platform that is composable, AI-native, flexible, and powered by a governed semantic layer, designed for the way modern enterprises deliver value.
GoodData is built for CIOs, product leaders, and data teams who need to innovate quickly while maintaining governance and compliance. Our platform gives teams the tools to deliver trusted AI, embedded analytics, and decision intelligence at enterprise speed.
The GoodData platform unifies semantic modeling, governance, analytics, and agentic AI into a single secure foundation. This enables enterprises to:
🚀 Design & deploy fast: Create custom agentic AI apps and intelligence workflows for any use case—delivered in days, not years.
🚀 Scale & expand effortlessly: Scale on demand without sacrificing cost, compute, or performance, while delivering multi-tenant embedded analytics and AI applications.
🚀 Customize flexibly: Modify everything with developer-first tools, SDKs, and an API-driven architecture.
🚀 Secure by design: Run trusted agents with enterprise-grade governance, security, and flexible deployment in the cloud or on-premises.
🚀 Leverage our expertise: Partner with our forward-deployed engineers to co-design, test, and deliver production-ready AI and analytics solutions.
We serve all industries worldwide, from fintech and retail to healthcare, SaaS, and manufacturing. More than 123,000 organizations and 3.9 million users rely on GoodData.
One AI platform, limitless ways to build, embed, and monetize intelligent analytics and AI agents. 👉 Start building smarter intelligence today at www.gooddata.com.
Rating Reviews
Rating is calculated based on
5
reviews and is evolving.
Pros: The best part was the opportunity to work on complex data analytics problems and contribute to a growing AI platform. There are many smart engineers, so learning is constant. The team collaboration was generally strong, and I appreciated the flexibility in working hours and the hybrid setup which made managing my schedule much easier. It's a good stepping stone for further career growth.
Cons: While there's great technical talent, sometimes project timelines felt a bit ambitious, leading to occasional crunch times. Communication between some departments could also be improved to ensure smoother project execution. The pay and benefits, while decent, didn't always feel competitive compared to some other tech roles in the current market.
Advice to Management: Consider standardizing some development processes and ensuring leadership communicates strategic shifts clearly to all teams to foster better alignment and reduce potential friction during ambitious projects.
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Pros: I've appreciated the focus on continuous learning and the opportunities to work with modern tech stacks within the data analytics industry. The team I worked with was generally supportive and collaborative. There's a good emphasis on problem-solving and contributing to the platform's evolution. For engineers looking to deepen their expertise in BI and SaaS, there are definitely avenues for growth.
Cons: Career progression can sometimes feel a bit unclear, with less structured paths than one might hope for. During peak project times, workload can become quite demanding, occasionally impacting work-life balance despite the remote setup. Communication from higher leadership about strategic direction could sometimes be more consistent to help align everyone's efforts effectively.
Advice to Management: Consider implementing more defined career pathing and performance review metrics. Enhancing communication from leadership on company strategy and roadmaps would also be beneficial for team alignment and motivation.
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Pros: I've appreciated the collaborative atmosphere and the opportunities to work on cutting-edge AI and analytics projects. The team is knowledgeable and supportive, and learning new technologies is encouraged. The flexibility to work remotely or in the modern Prague office is a big plus, contributing to a decent work-life balance.
Cons: While training is available, structured career paths aren't always clearly defined, which can make it a bit challenging to navigate advancement. Sometimes project priorities can shift quite rapidly, which can be disruptive. The pay and benefits are competitive but not outstanding compared to some larger tech firms.
Advice to Management: Consider implementing more transparent career progression frameworks and offering advanced skill development programs to help employees see clear paths for growth within the company.
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What's it like working in category management at GoodData.AI, especially with their focus on change management for clients?
In category management at GoodData.AI, I've found the role deeply involves understanding client needs for data-driven insights, which naturally supports their change management initiatives.
What is the working culture like at GoodData.AI for data analysts in Europe?
The culture at GoodData.AI feels very collaborative and focused on innovation, especially within their European offices. As a data analyst here, I appreciate the emphasis on continuous learning and the opportunity to work on cutting-edge AI projects in the tech industry.
What is the working culture like at GoodData.AI for data engineers in Europe?
At GoodData.AI, I've found the culture to be collaborative and focused on innovation, especially for roles like data engineers in our European offices. The company fosters a good work-life balance which is great for a growing tech company of our size.
What's it like to be a Category Manager at GoodData.AI, and what tools do you use for data analysis?
As a Category Manager at this enterprise tech company, I use GoodData.AI's platform daily for deep dives into sales performance and customer behavior, making data-driven decisions easier.
What is the typical salary range for a Data Engineer at GoodData?
As a Data Engineer at GoodData, I found the salary to be competitive within the data analytics industry, especially for a mid-sized tech company. Compensation was in line with market rates for similar roles in Prague, factoring in experience and the specific project.
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