GIS Technical Lead

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.