Publié il y a 9 mois
GIS Technical Lead
@ Querentia Inc.
Toronto, Ontario
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
| Niveau | Chef d’équipe |
| Domaine | Données et analytique |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
| Langues | English |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Querentia Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 331 |
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.
Journal
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