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Senior Product Manager - 26434

  • Calgary, AB, Canada
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Job details

Experience
7+ years of experience in product management, data science, data engineering, or another technical role building data or AI products.
Posting language
English
Posted

Original job description

Senior Product Manager - Enverus ONE Asset Library & Spaces

Why YOU want this position

At Enverus, we're committed to empowering the global quality of life by helping our customers make energy affordable and accessible to the world.

We are the most trusted energy-dedicated SaaS company, with a platform built to maximize value from generative AI, and our innovative solutions are reshaping the way energy is consumed and managed. By offering anytime, anywhere access to analytics and insights, we're helping our customers make better decisions that help provide communities around the world with clean, affordable energy.

The energy industry is changing fast. But we've continued to lead the way in energy technology, creating intelligent connections across the entire energy ecosystem, from renewables, power and utilities, to oil and gas and financial institutions. Our solutions create more efficient production and distribution, capital allocation, renewable energy development, investment and sourcing, and help reduce costs by automating crucial business operations. Of course, this wouldn't be possible without our people, which is why we have built a team of individuals from a diverse range of backgrounds.

Are you ready to help power the global quality of life? Join Enverus, and be a part of creating a brighter, more sustainable tomorrow.

About the role

We are seeking a technically deep Senior Product Manager to help make Enverus ONE, our AI platform for the energy industry, the place where customers bring together Enverus data, their own proprietary data, and their teams' expertise.

This role will help lead product for the Enverus ONE Asset Library, Asset Analyst, Collaboration, and Spaces initiatives. You will define how customers securely bring their own data into Enverus ONE, how that data connects with Enverus' foundational datasets across wells, land, infrastructure, and geospatial assets, and how teams use AI agents to research, analyze, and work together on top of it. You will work closely with engineering, data science, platform architecture, security, and data and product teams across Enverus whose datasets and domain expertise feed these experiences.

This is a hands-on product role for someone who is comfortable working close to the data and the architecture, and who enjoys taking ambiguous problems from discovery through delivery. Strong technical builders moving into product management are encouraged to apply.

What you will do

  • Own product requirements and roadmap priorities for Asset Library, Asset Analyst, Collaboration, and Spaces in Enverus ONE, in partnership with the Enverus ONE data strategy lead.
  • Define how customers securely bring proprietary data into Enverus ONE, including ingestion, connectors, permissions, data isolation, and governance.
  • Shape the data model that connects customer data with Enverus datasets across wells, land, production, infrastructure, and geospatial assets, including the entity resolution and linking logic that makes them work together.
  • Define requirements for agentic research and analysis workflows that reason across large structured, unstructured, and geospatial datasets using retrieval, APIs, and custom tools.
  • Define how teams collaborate in Spaces, including shared workspaces, sharing data, analyses, and agent outputs across users and organizations, with the right access controls.
  • Partner with data and product teams across Enverus to bring their datasets and domain expertise into Asset Library and Spaces, so these experiences reflect the full breadth of Enverus across oil and gas, power, renewables, and other energy markets.
  • Work with security and compliance teams so that features handling sensitive customer data meet SOC 2 and enterprise customer expectations.
  • Work directly with customers, internal analysts, and commercial teams to understand how they research and manage assets today, and translate those workflows into clear priorities.
  • Partner closely with engineering on technical design, and prototype with Python, SQL, and AI tools to test ideas before committing engineering capacity.
  • Establish clear measures for adoption, data onboarding time, data quality, and agent accuracy, and use them to prioritize investment.
  • Act as the internal product expert for these initiatives and clearly communicate current capabilities, gaps, priorities, and future direction.
  • Consistently identify new opportunities and drive them forward without requiring detailed direction from leadership.

What skills you should have

  • 7+ years of experience in product management, data science, data engineering, or another technical role building data or AI products.
  • Hands-on experience with large-scale data systems, automated data pipelines, or production ML and AI applications.
  • Working knowledge of agentic AI and LLM applications, including retrieval, tool use, and orchestration.
  • Experience building products on sensitive or proprietary customer data, with an understanding of data security, privacy, and access control practices such as SOC 2.
  • Demonstrated ability to take ambiguous problems and turn them into concrete plans and shipped outcomes.
  • Ability to work across teams and influence without direct authority, especially when success depends on data and expertise owned by other groups.
  • Strong ownership mentality and bias toward action.
  • Proven problem-solving skills with an ability to synthesize complex information and communicate it clearly to technical and non-technical audiences.
  • Strong customer orientation and interest in understanding how users make decisions with energy and asset data.
  • Bachelor's or advanced degree in Engineering, Computer Science, Geoscience, Physics, Data Science, or a related field.
  • Excellent interpersonal and communication skills, strong attention to detail, self-motivated with a strong work ethic.

Skills that stand out

  • Experience with oil and gas, land, well, or geospatial data, and familiarity with how operators, mineral owners, and investors use it.
  • Familiarity with Enverus products and data, or with comparable energy data platforms.
  • Experience with graph-based data models, knowledge graphs, or geospatial algorithms.
  • Experience building collaborative, multi-tenant, or bring-your-own-data software products.
  • Technical fluency with Python, SQL, cloud platforms (AWS, GCP, or Azure), and modern data and ML tooling.

This role is eligible for: Variable Compensation

More about this job

Responsibilities

The Senior Product Manager will own the product requirements and roadmap for the Enverus ONE platform, focusing on asset library, collaboration, and AI-driven analysis initiatives. They will partner with engineering and data teams to define data models, ingestion workflows, and agentic research capabilities while ensuring compliance with security standards.

Requirements

Candidates must have 7+ years of experience in product management or technical roles building data or AI products, with hands-on experience in large-scale data systems and ML applications. A bachelor's or advanced degree in a technical field such as Engineering, Computer Science, or Data Science is required.

Skills

  • Product management
  • Data science
  • Data engineering
  • AI
  • Machine learning
  • Agentic AI
  • LLM
  • Python
  • SQL
  • Data security
  • Privacy
  • SOC 2
  • Geospatial data
  • Cloud platforms
  • Data modeling
  • Product roadmap

Benefits

  • Variable compensation

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Data & Analytics
  • Energy
  • Management & Leadership

Keywords

  • Product Management
  • Enverus ONE
  • AI Platform
  • Energy Industry
  • SaaS
  • Generative AI
  • Asset Library
  • Data Ingestion
  • Data Governance
  • Agentic AI
  • LLM
  • Python
  • SQL
  • SOC 2
  • Geospatial Data
  • Cloud Platforms
  • AWS
  • GCP
  • Azure
  • Machine Learning
  • Data Pipelines
  • Knowledge Graphs
  • Multi-tenant
  • Product Roadmap
  • Entity Resolution
  • Data Modeling
  • Collaboration
  • Energy Markets
  • Technical Design
  • Analytics

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