Posted 9 months ago
Technical Lead
@ Querentia Inc.
Toronto, Ontario
Overview
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.
Responsibilities:
- 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
Requirements summary:
- 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
Tools & skills
Source and dates
Source type not verified · jsonld
- Employer posting date
- 2026-01-25
- First seen by our source
- 2026-10-26
- Source record updated
- 2026-11-02
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Lead |
| Department | Data & analytics |
| Work setting | Office, Client sites |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Querentia Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 331 |
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.
Journal
Only you can see this. Kept on this device, and in your account when you sign in.