Product Manager - Aura Graph Analytics

As a Product Manager at Neo4j, you will be responsible for understanding customer needs, collaborating with engineering teams to develop products, and enhancing the user experience for data scientists and analysts. You'll also conduct market research to inform product strategy and work with cross-functional teams to bring innovative solutions to market.

To become a Product Manager at Neo4j, you should have at least 8 years of professional experience with a minimum of 3 years in product management. A solid understanding of cloud platforms, data analytics, and modern programming, such as Python, is essential. Familiarity with technologies like Spark and NoSQL databases is also advantageous.

Yes! Neo4j offers flexible working conditions including remote positions from various locations across Europe such as France, Germany, Italy, the Netherlands, Spain, and more. This allows you to work in a way that suits your lifestyle while contributing to our global efforts in data analytics.

A successful Product Manager at Neo4j should possess excellent communication skills, the ability to synthesize inputs, and experience with cloud service offerings in data analytics. You'll also need a strong background in data science and the ability to work collaboratively with cross-functional teams.

At Neo4j, we are committed to fostering an inclusive and empowering environment where Product Managers can thrive. With opportunities for professional development, mentorship programs, and a supportive culture, we encourage our team members to grow and advance their careers while making impactful contributions.

To understand customer needs, I prioritize techniques like user interviews, feedback surveys, and data analysis of usage patterns. Engaging with current users and collaborating with customer support teams provides valuable insights into pain points and desired features.

Certainly! One of my notable projects involved developing a data analytics tool where I coordinated between engineering, design, and marketing teams. We conducted user testing and utilized agile methodologies to refine the product which resulted in a successful launch and positive user feedback.

I take a comprehensive approach to market research by analyzing industry trends, competitor offerings, and customer feedback. I ensure to use both qualitative and quantitative data to make informed decisions about product direction and strategy.

Prioritizing features involves balancing customer feedback, potential business impact, and technical feasibility. I utilize frameworks such as the MoSCoW method to categorize features into must-haves, should-haves, could-haves, and won't-haves for clear decision-making.

I have extensive experience with various cloud platforms including AWS, Google Cloud, and Azure. I’ve worked on developing and integrating products that leverage serverless computing, ensuring scalability and efficiency in data processing.

Handling conflicts requires open communication and active listening. I encourage team members to express their perspectives and work collaboratively toward a mutual understanding. I find that fostering a culture of respect and shared goals goes a long way in resolving conflicts.

Data is central to my product management approach. I rely on analytics to inform product decisions, validate ideas, and measure success. By leveraging data, I can make more objective choices and adapt product strategies based on real user behavior.

To ensure alignment, I actively participate in strategic planning sessions and continuously engage with leadership across departments. I also keep the team's focus on the company's core values and mission, making sure our product goals integrate seamlessly with the broader vision.

My strategies for launching new features include thorough testing, a clear communication plan, and gathering actionable feedback post-launch. I promote features through targeted marketing efforts and ensure support teams are well-equipped to assist users with questions.

After a product launch, I measure success through key performance indicators (KPIs) such as user engagement, adoption rates, and customer satisfaction. I also gather qualitative feedback to assess whether the product meets user expectations and requirements.