Our technology has no boundaries! NVIDIA is creating the worlds most groundbreaking and innovative compute platforms for the world to use! Its because of our work that data engineers and data scientists can advance their ideas. We are looking for individuals to develop a GPU accelerated data processing and ML platform for data scientists to use. In this role, you'll lead and encourage adoption of the data processing service, your work should improve time to first query (TTFQ), QPS metrics, drive platform engagement metrics, and come up with innovative solutions that blends with groundbreaking NVIDIA's enterprise scale data science platform.
What youll be doing:
Define and Champion the Vision: Own the product vision, strategy, and roadmap for our data platform, ensuring alignment with overall company objectives and anticipating future data needs.
Deeply Understand User Needs: Conduct extensive user research, collect requirements from data engineers, data scientists, analysts, and business customers to identify problems, opportunities, and unmet needs.
Translate Needs into Actionable Requirements: Translate sophisticated business and technical requirements into detailed product specifications, user journeys, and acceptance criteria for engineering teams.
Prioritize and Manage the Backlog: Drive product prioritization, balancing new feature development, technical debt, and platform stability, while continuously refining and grooming the product backlog.
Collaborate Cross-Functionally: Work seamlessly with engineering, design, and data teams throughout the product lifecycle, from ideation and development to launch and iteration.
Drive Data Governance and Quality: Promote standard processes to uphold data quality, governance, security, and compliance within the platform, safeguarding data integrity and trustworthiness.
Go-to-Market Strategy and Adoption: Develop and execute go-to-market strategies, including internal communication, documentation, training, and evangelism to drive platform adoption and increase value for users.
Monitor and Iterate: Define KPIs to measure product performance, analyze usage data, and leverage insights to advise future product improvements and iterations.
Stay Ahead of the Curve: Monitor industry trends, competitive landscapes, and new technologies in data engineering, machine learning, and AI to find opportunities for platform evolution.
What we need to see:
5+ years of product management experience, with a strong focus on data platforms, data infrastructure, or large-scale data products.
Deep understanding of data engineering concepts and technologies, including big data processing (e.g., Spark, Hadoop), data warehousing, data lakes (e.g., Delta Lake), ETL/ELT pipelines, and streaming data.
Familiarity with cloud data platforms such as Databricks, Snowflake, AWS EMR, Google Dataproc. Experience with their features, strengths, and weaknesses is a significant plus.
Experience with machine learning (ML) and AI concepts and how data platforms support the entire ML lifecycle (feature stores, model training, inference, MLOps).
Proven track record to define product vision and strategy, translate it into a detailed roadmap, and execute with strong results.
Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
Strong analytical and problem-solving skills, with a data-driven approach to decision-making.
Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience). Master's degree highly preferred.
Ways to stand out from the crowd:
Prior data processing at scale on NVIDIA GPUs
Experience building or managing products excelling in developer experience (DX)
Our technology has no boundaries! NVIDIA is creating the worlds most groundbreaking and innovative compute platforms for the world to use! Its because of our work that data engineers and data scientists can advance their ideas. We are looking for individuals to develop a GPU accelerated data processing and ML platform for data scientists to use. In this role, you'll lead and encourage adoption of the data processing service, your work should improve time to first query (TTFQ), QPS metrics, drive platform engagement metrics, and come up with innovative solutions that blends with groundbreaking NVIDIA's enterprise scale data science platform.
What youll be doing:
Define and Champion the Vision: Own the product vision, strategy, and roadmap for our data platform, ensuring alignment with overall company objectives and anticipating future data needs.
Deeply Understand User Needs: Conduct extensive user research, collect requirements from data engineers, data scientists, analysts, and business customers to identify problems, opportunities, and unmet needs.
Translate Needs into Actionable Requirements: Translate sophisticated business and technical requirements into detailed product specifications, user journeys, and acceptance criteria for engineering teams.
Prioritize and Manage the Backlog: Drive product prioritization, balancing new feature development, technical debt, and platform stability, while continuously refining and grooming the product backlog.
Collaborate Cross-Functionally: Work seamlessly with engineering, design, and data teams throughout the product lifecycle, from ideation and development to launch and iteration.
Drive Data Governance and Quality: Promote standard processes to uphold data quality, governance, security, and compliance within the platform, safeguarding data integrity and trustworthiness.
Go-to-Market Strategy and Adoption: Develop and execute go-to-market strategies, including internal communication, documentation, training, and evangelism to drive platform adoption and increase value for users.
Monitor and Iterate: Define KPIs to measure product performance, analyze usage data, and leverage insights to advise future product improvements and iterations.
Stay Ahead of the Curve: Monitor industry trends, competitive landscapes, and new technologies in data engineering, machine learning, and AI to find opportunities for platform evolution.
What we need to see:
5+ years of product management experience, with a strong focus on data platforms, data infrastructure, or large-scale data products.
Deep understanding of data engineering concepts and technologies, including big data processing (e.g., Spark, Hadoop), data warehousing, data lakes (e.g., Delta Lake), ETL/ELT pipelines, and streaming data.
Familiarity with cloud data platforms such as Databricks, Snowflake, AWS EMR, Google Dataproc. Experience with their features, strengths, and weaknesses is a significant plus.
Experience with machine learning (ML) and AI concepts and how data platforms support the entire ML lifecycle (feature stores, model training, inference, MLOps).
Proven track record to define product vision and strategy, translate it into a detailed roadmap, and execute with strong results.
Excellent communication, interpersonal, and presentation skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.
Strong analytical and problem-solving skills, with a data-driven approach to decision-making.
Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience). Master's degree highly preferred.
Ways to stand out from the crowd:
Prior data processing at scale on NVIDIA GPUs
Experience building or managing products excelling in developer experience (DX)
You will also be eligible for equity and benefits . NVIDIA accepts applications on an ongoing basis.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.NVIDIA is the world leader in accelerated computing.
NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society.
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