Product Manager (Data Products)

Amtex Systems Inc is an information technology and talent solutions company offering talent and BI consulting to the companies in US for over 25 years.

Our solutions are designed to fill resource gaps, by providing the right candidates who deliver value to the organization. Our propensity to nurture and build strong relationships with our clients helps us better understand their business demands and gives us the ability to provide services that are on time and rise above the rest.

 

Job Title: Product Manager (Data Products)

Level: Junior to Mid level

Job Location: Sunnyvale, CA (Hybrid / Office Presence Preferred)

Job Type: Full-time Permanent

Job Description:

We are looking for a Product Manager focused on data products who thrives in an early-stage, hands-on environment. In this role, you will own the product lifecycle from 0 to 1, bridge the gap between users and engineering teams, and leverage modern AI tools to accelerate development.

Key Responsibilities:

• 0 to 1 Product Development: Build, launch, and scale native GenAI data products from conception to execution.
• Cross-Functional Execution: Collaborate closely with engineering teams to prioritize tasks, translate technical user feedback into actionable roadmaps, and articulate complex concepts clearly.
• AI-First Workflow Integration: Utilize cutting-edge AI coding tools (e.g., Claude Code, Cursor) and generative AI concepts in daily product workflows.
• Data Stack Optimization: Leverage a deep understanding of the modern data stack to design solutions for technical users.

Requirements:

Experience & Background:

• 2-3+ years of product management experience.
• Startup Experience: Prior PM experience in an early-stage startup environment (Seed to Series B).
• Product Launch: Proven track record of building and launching technical products from 0 to 1.
• Technical Roots: Background as a data engineer preferred (not data science or data analytics-heavy backgrounds).
• Education: Technical degree in Computer Science, Mathematics, or a related quantitative field.

Technical Expertise:

• Modern Data Stack: Deep familiarity with data engineering processes, ELT, data warehousing, orchestration tools, dbt, Snowflake, and Spark.
• Data & Querying: High proficiency in SQL and the ability to articulate technical concepts to engineers.
• Artificial Intelligence: Hands-on experience with native GenAI products (not just bolted-on AI features), Large Language Models (LLMs), RAG architectures, and AI evaluation metrics.
• AI Tooling: Active, daily use of AI coding assistants and workflows.

Traits & Soft Skills:

• High intellectual curiosity, adaptability, and a rapid learning curve for emerging AI advancements.
• Thrives in ambiguous, fast-paced environments requiring a self-starter approach with minimal top-down direction.
• Collaborative and deeply respectful team player.