Gridsight is a rapidly growing Grid/CleanTech startup on a mission to accelerate global electrification and decarbonisation. We are building a vertical SaaS platform for electricity utilities, enabling them to modernise grid operations and unlock transformational capabilities such as dynamic operating envelopes and flexible interconnections. Having recently raised our Series A funding from Airtree Ventures, Energy Transition Ventures and Area VC, we are poised for rapid growth and are seeking talented individuals to join us on our mission.

As a Senior Customer Data Engineer, you'll lead the technical and people aspects of Gridsight’s customer data initiatives. You’ll own the design, development, and optimisation of critical data pipelines across diverse utility environments, working hand-in-hand with customer-facing teams. This is a highly visible role that combines technical depth, operational excellence, and people leadership to enable the success of Gridsight’s most strategic utility partners.

Key Responsibilities:

• Lead by example: Architect, develop, and maintain scalable, production-grade ETL pipelines to integrate large volumes of utility data (e.g., meter, GIS) into Gridsight’s platform.
• Own the end-to-end lifecycle of customer data pipelines—including ingestion, transformation, monitoring, and issue resolution—with a focus on reliability and performance.
• Collaborate cross-functionally with Data Science, Commercial Operations, and Customer Success teams to deeply understand customer needs and proactively deliver solutions.
• Ensure data quality by implementing robust validation, governance, and pipeline monitoring practices.
• Optimise system performance by tuning queries, data models, and ingestion processes for efficiency and low latency.
• Drive continuous improvement across tooling, standards, and best practices within the Customer Data Engineering team.
• Contribute to technical strategy for customer data engineering, influencing architectural decisions and scaling initiatives as Gridsight grows.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related discipline.
• 5+ years of professional experience in Data Engineering or similar roles, ideally including customer-facing or externally impactful projects.
• Previous people management or technical leadership experience (formal or informal); you enjoy growing others while staying close to the work yourself.
• Deep experience building and maintaining production-quality ETL pipelines.
• Strong command of SQL and relational databases; familiarity with dbt is a plus.
• Hands-on experience with big data frameworks (Databricks or Spark preferred) and cloud computing platforms (AWS strongly preferred).
• Proficiency in Python, Git, and working comfortably in command-line environments.
• Strong problem-solving skills with a proactive attitude toward identifying and fixing technical challenges.
• Exceptional communication and collaboration skills—you know how to bring technical and non-technical stakeholders along for the journey.
• Self-starter mentality with excellent time management and prioritization skills, especially in fast-paced, ambiguous environments.

What We Offer:

• Join a rapidly scaling venture-backed company on the first floor.
• Highly competitive salary and equity package.
• Flexible, hybrid working environment with a high performing, mission-driven team.