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Publié il y a 9 mois

GIS Technical Lead

@ Querentia Inc.

Toronto, Ontario

TélétravailContrat
Postuler
SIGNAUX

En bref

Querentia Inc. is hiring a contract GIS Technical Lead to drive data-intensive projects combining data engineering and data science in the utilities and energy sector. The work covers structural, GIS and time-series (AMI) data, mentoring junior staff, and liaising with stakeholders and product teams.

Responsabilités :

  • Lead requirements gathering with business stakeholders and SMEs
  • Lead data science and data engineering teams on integrated AI solutions
  • Oversee ingestion of structural, GIS and AMI data
  • Design validation frameworks for platform outputs
  • Mentor junior data scientists and engineers

Résumé des exigences :

  • Proven experience leading data engineering and data science projects
  • Hands-on experience with GIS, structural and time-series data
  • Strong stakeholder communication and presentation skills
  • Working knowledge of AWS or other cloud services for data and MLOps
  • Utilities or energy sector experience is an asset

Outils et compétences

Source et dates

Type de source non vérifié · jsonld

Date publiée par l’employeur
2026-02-17
Première détection par notre source
2026-10-26
Mise à jour du dossier source
2026-11-09

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauChef d’équipe
DomaineDonnées et analytique
Milieu de travailBureau
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
LanguesEnglish

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

ChampValeur
Offres sur Jobsy331
Description

Role Overview

We are seeking an experienced Technical Lead to drive complex, data-intensive projects combining Data Engineering and Data Science within the utilities and energy domain. This role requires hands-on leadership across large-scale datasets (including GIS and time-series data), strong stakeholder engagement skills, and experience delivering integrated AI-driven solutions.

The successful candidate will act as a technical liaison across business stakeholders, product teams, and engineering teams, ensuring high-quality, scalable, and business-aligned data solutions.

Key Responsibilities

• Lead technical requirements gathering sessions with business stakeholders and subject matter experts to translate business needs into detailed technical specifications and data models.

• Lead the technical execution of projects involving both Data Science and Data Engineering teams to deliver integrated AI solutions.

• Oversee the end-to-end data lifecycle, including data contextualization, mapping, and ingestion of large-scale structural, GIS, and time-series (e.g., AMI) data into the product.

• Configure and customize demand forecasting and grid impact assessment modules using backend interfaces and front-end UI controls to align with client requirements.

• Design and implement rigorous validation frameworks to ensure the accuracy, reliability, and business value of platform outputs.

• Provide technical guidance, mentorship, and support to junior data scientists and engineers.

• Serve as a key technical liaison, communicating project status, risks, technical complexities, and outcomes to internal stakeholders and product teams.

Required Experience & Skills

• Proven experience leading technical projects with significant Data Engineering and Data Science components.

• Demonstrated experience mentoring and providing technical leadership to junior team members.

• Hands-on experience working with large, complex datasets including:

• Structural data (e.g., asset records)

• Geospatial (GIS) data

• Time-series data (e.g., smart meter readings)

• Strong stakeholder communication and presentation skills, with the ability to translate technical concepts for non-technical audiences.

• Working knowledge of AWS (or other cloud-based services) relevant to data processing and MLOps.

Nice-to-Have Qualifications

• Domain experience in utilities, power systems, or the broader energy sector.

• Experience collaborating closely with product teams to implement and configure vendor platforms.

• Experience establishing data quality frameworks and governance processes.

• Experience acting as the technical point-of-contact for third-party software vendors.

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