Environmental Data Manager

Talon Metals Corp

  • MN
  • 12 days ago
  • Remote

    Highlights

    As Talon continues to grow as a company, the role may be required to support other projects, including but not limited to Eagle Mine, Michigan Exploration and the Battery Metals Processing Facility, where needed. Collaboration - Works effectively across technical disciplines, consultants, contractors, and internal stakeholders to encourage alignment and avoid siloed decision-making.

    Numbers & Facts

    LocationMN (
    Remote
    )

    Description

    Talon Metals Corp 165 N Warren Street Tamarack, MN 55787

    JOB TITLE: Environmental Data Manager

    LOCATION: TBD - Remote Opportunities Available

    DEPARTMENT: Tamarack Project, Environmental

    MAIN PURPOSE:

    The Environmental Data Manager is responsible for managing and parsing environmental data sets for the Tamarack Underground Project. As Talon continues to grow as a company, the role may be required to support other projects, including but not limited to Eagle Mine, Michigan Exploration and the Battery Metals Processing Facility, where needed.

    MAIN RESPONSIBILITIES/ACTIVITIES:

    • Lead by example, demonstrating commitment to Talons core values: Safety, Respect, Integrity, Adaptability, and Achievements.
    • Support preparation of technical reports, internal and external presentations, regulatory submissions, and procurement documentation, as required.
    • Manage environmental databases, incoming data validation, and staff access policies.
    • Administer digital collection platforms, laboratory coordination, and automated data reporting and loading.
    • Consults with subject matter experts on data management and quality implications in their work.
    • Designs and deploys automated workflows and organizational safe-use frameworks.
    • Provides cross-departmental data management support.
    • Educates staff on data quality management practices.
    • Perform other duties as assigned.

    EDUCATION, QUALIFICATIONS AND EXPERIENCE:

    • Degree in computer science, data management, engineering or sciences.
    • 5-15 years of experience managing environmental databases.
    • Extensive knowledge of laboratory deliverables and methods.
    • Strong understanding of environmental sampling data and data management.
    • Fluent with Quality Assurance and Quality Control procedures for environmental sampling.
    • Advanced knowledge of database management and administration
    • Hands-on experience with EQuIS database operations
    • Proficiency in coding and scripting languages used for data management and automation.
    • Strong analytical abilities and effective communication skills.
    • Proficient in manipulating, transforming, and managing structured data (joins, filtering, aggregation, etc.)

    KEY PERSONAL COMPETENCIES:

    • Safety Leadership - Consistently considers health, safety, environmental, and community impacts in engineering decisions and project recommendations.
    • Technical Judgment - Applies sound data management principles, practical mining or environmental experience, and risk-based thinking to develop fit-for-purpose solutions.
    • Action Oriented - Takes initiative, addresses issues in a timely manner, and drives work forward with limited supervision.
    • Collaboration - Works effectively across technical disciplines, consultants, contractors, and internal stakeholders to encourage alignment and avoid siloed decision-making.
    • Communication - Communicates clearly, concisely, and professionally through written reports, technical reviews, presentations, and day-to-day interactions.
    • Decision Quality - Considers technical, safety, cost, schedule, permitting, operational, and execution trade-offs when making recommendations.
    • Accountability / Managing Ambiguity - Follows through on commitments, escalates risks appropriately, and remains effective in a dynamic project environment where information may be incomplete or evolving.
    • Project management skills would be an asset.
    • Familiarity with data quality documentation and formal data validation is an asset.

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