Technical Product Manager, Data & Analytics Platform

Mariana Minerals is hiring a Technical Product Manager to serve as the single product owner for its data engineering family, spanning the data platform, analytics, data science, and AI and agentic workflows. The role focuses on bringing structure to cross-disciplinary work, shaping the roadmap and specifications, and driving adoption as prototypes mature into supported software.

Location and Work Mode

San Francisco, CA (hybrid)

Compensation

USD 115,000 - 208,000 per year

Responsibilities

• Maintain constant communication with internal teams, including operators, machine learning engineers, software developers, analysts, and data users, so their needs guide the roadmap.
• Own the roadmap for the data platform, analytics, and data science tooling, defining what is built next, for whom, and why.
• Produce product specifications, KPIs, and success metrics that translate ambiguous requests into scoped, shippable work.
• Lead prioritization and stakeholder alignment to keep engineering teams focused on deep technical execution.
• Make build-vs-buy decisions for BI and analytics and prioritize tooling that enables stakeholders to answer their own questions without adding headcount.
• Define where agents belong versus conventional software and drive AI and agentic workflows from demo to adopted tooling.
• Decide which new data streams are integrated, when they are integrated, and the standards to apply as new sensors and sources come online.
• Set standards for what “supported” and “correct” mean as tools move beyond scripts and spreadsheets, including explicit guidance on what will not be migrated.

Requirements

• 4–8+ years in technical product management, data platform, or analytics product roles, or equivalent experience leading cross-disciplinary technical programs.
• Ability to operate as the only PM in a highly technical environment, knowing when to drive decisions, when to defer to engineers, and how to build credibility.
• Depth in data infrastructure and analytics sufficient to earn trust from data engineers, data scientists, and analysts, including the judgment to recognize when a technical answer is appropriate.
• Working fluency with the current LLM and foundation-model landscape, including how to evaluate agentic approaches versus conventional software.
• A track record of structuring ambiguous, cross-functional initiatives, aligning stakeholders, and owning end-to-end outcomes.
• Capability to prototype hands-on, producing a PoC with stakeholders rather than limiting work to requirements.
• Strong prioritization and tradeoff judgment, with the ability to say no in a visible and consistent way.
• Exceptional written and verbal communication across technical and non-technical audiences, from data engineers and operators to executives.

Technologies

• LLM
• Foundation-model
• Hex
• Looker

Nice to Have

• Product ownership of a data platform, warehouse, or analytics stack in production.
• Experience with BI and analytics tooling strategy, including Hex, Looker, or embedded analytics.
• Experience shipping LLM-powered or agentic internal tools.
• Background in mining, energy, chemicals, manufacturing, or other heavy industry.
• Experience leading transitions from spreadsheets and scripts to supported software.

How You’ll Operate

• Structure from ambiguity: Bring direction to cross-disciplinary initiatives and align stakeholders rather than waiting for direction.
• Ruthless, visible prioritization: Clearly state what will not be worked on, not just what will.
• Hybrid Pioneer/Settler: Build initial prototypes with stakeholders, then develop the roadmap to validate the use case and move to production if it proves valuable.
• Ecosystem fluency: Understand how Mariana’s data fits into the systems that consume it and how it relates to the frontier of LLM capability, keeping prioritization well-calibrated.

Benefits

• Compensation Range: $115K - $208K

Culture

• Everyone Gets Home Safe: Never put speed or cost ahead of people.
• Extreme Ownership: Take full responsibility for outcomes and relentlessly drive toward solutions.
• Engineer Out Requirements, then Automate: Simplify, optimize, and automate for scale.
• Share Your Legos: Collaborate openly, share knowledge, and empower each other to build bigger, better solutions.