Technical Lead
About the role
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.
This engagement is managed end-to-end by Querentia. Our recruiters give you honest feedback at every stage, prepare you for the interview, and support a smooth onboarding once you land the offer.