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Publié il y a 9 mois

Technical Lead

@ Querentia Inc.

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Toronto, Ontario

TélétravailContrat
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SIGNAUX

En bref

Querentia Inc. is hiring a Technical Lead on a contract basis to drive end-to-end delivery of data and AI solutions. The role bridges data engineering, data science and business stakeholders, covering large structural, GIS and time-series datasets, and mentoring junior team members.

Responsabilités :

  • Lead requirements gathering with business stakeholders and SMEs
  • Oversee end-to-end data lifecycle for structural, GIS and AMI data
  • Configure demand forecasting and grid impact assessment modules
  • Design validation frameworks for platform outputs
  • Mentor junior data scientists and engineers

Résumé des exigences :

  • Proven experience leading projects with data engineering and data science components
  • Hands-on experience with large structural, GIS and time-series datasets
  • Experience mentoring junior team members
  • Strong stakeholder communication and presentation skills
  • Working knowledge of AWS or other cloud services for data and MLOps

Outils et compétences

AWSGIS software
Source et dates

Type de source non vérifié · jsonld

Date publiée par l’employeur
2026-01-25
Première détection par notre source
2026-10-26
Mise à jour du dossier source
2026-11-02

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, Chez les clients
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.

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Description

Objective

We are seeking a Technical Lead to drive the end-to-end delivery of advanced data and AI-driven solutions by bridging Data Engineering, Data Science, and business stakeholders. This role will lead complex technical initiatives involving large-scale structural, GIS, and time-series data, ensuring scalable data architectures, high data quality, and accurate analytical outputs. The Technical Lead will provide hands-on leadership, mentor junior team members, and serve as a key technical liaison to ensure solutions align with business objectives and deliver measurable value.

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 the demand forecasting and grid impact assessment modules, using both backend interfaces and front-end UI controls, to align with client's specific needs.

• Design and implement rigorous validation frameworks to confirm the accuracy and business value of the platform's outputs.

• Provide technical guidance, mentorship, and support to junior data scientists and engineers, fostering their growth and ensuring high-quality deliverables.

• Serve as a key technical liaison, effectively communicating project status, technical complexities, and results to internal stakeholders and the product team.

Must-Haves:

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

• Demonstrated experience providing technical guidance and mentorship to junior team members.

• Hands-on project leadership experience working with large, complex datasets, including structural data (e.g., asset records), geospatial (GIS) data, and time-series data (e.g., smart meter readings).

• Excellent stakeholder communication and presentation skills, with the ability to articulate technical details to both technical and non-technical audiences.

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

Nice-to-Haves:

• Domain knowledge in the utility, power systems, or broader energy sector.

• Previous experience working closely with a product team to implement and configure a vendor platform or product.

• 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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