Remote Snowflake Jobs in Berkeley, CA (NOW HIRING)

Location: Remote (U.S.)
Job Type: Full-Time
Compensation: $180,000 – $230,000 Base Salary + Equity

About the Role

We're looking for a highly technical Senior Product Manager to lead our internal data platform and tooling initiatives. This is an individual contributor role partnering closely with engineering and data science to build the systems that power the business behind the scenes.

Unlike customer-facing product roles, you'll own internal data products and infrastructure, working directly with technical teams to improve data pipelines, internal tooling, and platform capabilities. This role is ideal for someone with an engineering background who transitioned into Product Management and enjoys solving deeply technical problems.

What You'll Do

• Own the roadmap for internal data platform products and technical infrastructure.
• Partner daily with engineering and data science teams to define priorities and deliver high-impact solutions.
• Lead products through the full product lifecycle—from discovery and planning through launch and continuous iteration.
• Define technical requirements and write detailed product specifications for internal platforms and data systems.
• Drive initiatives involving data ingestion, normalization, transformation, modeling, and large-scale data pipelines.
• Collaborate with engineering to improve internal tooling, automation, and platform scalability.
• Prioritize work based on technical complexity, business impact, and engineering trade-offs.
• Translate complex technical concepts into clear product strategy and execution plans.
• Work directly with executive leadership in a highly collaborative, startup environment.

Required Qualifications

• Product Management experience in a highly technical environment, with demonstrated ownership of complex products.
• Previous hands-on engineering experience is required, including roles such as:
  • Software Engineer
  • Data Engineer
  • Machine Learning Engineer
  • Data Scientist
  • Highly Technical Data Analyst
  • Experience at a startup, with the current or most recent role at a high-growth startup (Series B/C preferred).
• Experience owning products involving:
  • Internal tooling
  • Data platforms
  • Large-scale data pipelines
• Strong understanding of production data ingestion, transformation, normalization, and modeling.
• Authorized to work in the United States.

Technical Qualifications

• Python
• AWS
• Golang

• PostgreSQL
• OpenSearch
• Amazon Redshift
• Spark
• Databricks
• Snowflake
• BigQuery

• Production data pipelines
• Data ingestion
• Data transformation
• Data modeling
• Internal platform development

Experience with complex, API-driven products or data-intensive platforms is highly desirable.

Preferred Qualifications

• Experience in FinTech, payments, fraud prevention, identity verification, cybersecurity, or other highly technical domains.
• Founder or entrepreneurial experience.
• Strong startup mindset with a high level of ownership.
• Experience working directly alongside engineering and data science teams.
• Ability to communicate technical concepts effectively with executive leadership.

What We're Looking For

The ideal candidate is an engineer at heart who has successfully transitioned into Product Management. You're comfortable discussing architecture with engineers, prioritizing technical work, and driving execution across cross-functional teams.

Successful candidates will demonstrate:

• Strong technical depth and product judgment.
• Startup mentality with a bias toward action.
• Exceptional ownership and accountability.
• Excellent communication skills with engineers and executive stakeholders.
• Passion for solving complex technical problems.
• Genuine interest in building internal platforms rather than customer-facing products.

Candidates Unlikely to Be a Fit

The following backgrounds generally do not align with this opportunity:

• Product Managers whose experience is exclusively customer-facing and who are not interested in internal platform work.
• Candidates with only Big Tech or large enterprise/banking experience.
• Traditional Product Managers without prior engineering or technical experience.
• Technical professionals looking to transition into Product Management without prior PM ownership.
• Candidates whose resumes emphasize AI/ML buzzwords without meaningful experience in data platforms or internal tooling.
• Professionals with job tenures under two years or a history of frequent job changes.