Customer Data Engineer

Electricity grids are undergoing the most significant transformation in a century. The shift to renewables, the proliferation of rooftop solar, batteries, and EVs, and the increasing complexity of distribution networks are forcing utilities to operate their grids in fundamentally new ways. Gridsight is the analytics platform that makes this possible. 

Gridsight is a rapidly growing GridTech startup dedicated to accelerating global electrification and decarbonization. We are an AI-powered vertical SaaS platform that enables electric utilities to modernize grid operations, accelerate DER interconnection, and unlock dynamic grid capacity. The opportunity is enormous.

Why Now

Gridsight was founded in Australia five years ago. Since then, we’ve established a strong product–market fit and emerged as the category leader. We are now scaling rapidly across the US with multiple Top 20 utilities.

This role exists because we're growing faster than our current implementation process, and we need someone who can both roll up their sleeves to deliver today and help us build the tooling and process that makes tomorrow faster.

You'll be working at the intersection of delivery and data — close to customers, close to the commercial team, and close to the product and engineering decisions that shape what we build next.

Our Customer Data Engineers own data integration with our customers, ensuring they get value from Gridsight's platform quickly and seamlessly. You'll work directly with utility customers to understand their data environments, guide them through Gridsight's requirements, and lead the technical work of getting their data into the platform. You'll also contribute to the internal tooling that makes the next implementation faster and to the product work that accelerates time-to-value.

You'll spend roughly half your time in conversations with customers, half heads-down wrangling data, running transforms, and configuring the system. 

Gridsight runs an AI-forward stack that gives data engineers access to best-in-class tooling across data infrastructure, orchestration, and AI-assisted development, including: Databricks, dbt, Dagster, AWS, and enterprise Claude Code. Staying ahead of the curve is part of the job.

Customer Implementations (~80%)

• Lead end-to-end data implementation engagements with utility customers, from running workshops to scope data requirements through to live data flowing in the platform.
• Set up and configure data infrastructure in line with Gridsight's current implementation process.
• Map incoming customer data to Gridsight's schemas, develop code to transform customer data, and validate outputs against quality standards.
• Review incoming customer data against expected schemas and quality standards, providing clear and constructive feedback on issues.
  
• Run and monitor the data pipelines required to deliver a successful implementation.
• Drive customer data deliveries to completion. Triage and unblock issues, communicate clearly with customers and internal stakeholders, and maintain momentum. 
• Manage complex implementation situations with composure; maintain momentum and tight timelines, incomplete data, shifting priorities, and competing demands. 

Product Support (~20%)

• Identify and communicate patterns across customer engagements to inform product direction.
• Partner with Gridsight's data engineering team to productize implementation and transformation logic — turning bespoke code into repeatable, platform-ready tooling.
• Scope the data requirements needed to enable new product capabilities.
• Contribute to internal documentation, playbooks, and tooling that improve the efficiency and consistency of future implementations.
• Bring a tool-first mindset to the work: spot manual steps that can be automated, and take initiative to improve them.

• 4+ years of professional experience in data engineering, analytics engineering, technical consulting, or a similar role that combines hands-on data work with direct customer or stakeholder engagement.
• Advanced SQL skills and demonstrated ability to analyse, validate, and wrangle complex or messy datasets.
• Proficiency in Python for data transformation, validation, and scripting.
• Experience with dbt or similar ELT/ETL frameworks and working within data pipelines.
• Ability to lead customer-facing technical engagements — managing expectations, communicating data requirements clearly, and driving deliveries to completion.
• Experience with cloud data infrastructure and modern development practices (Git, command-line environments, collaborative codebases).
• A track record of building internal tools, leveraging AI-assisted development tooling or automating manual work to improve process efficiency. 
• Comfort with ambiguity — customer data environments are varied and there won't always be a playbook.
• Proactive and self-directed — you see what needs doing and drive it to completion without close supervision.

• Rapidly scaling venture-backed company on the ground floor.
• Highly competitive salary, equity, and comprehensive benefits package. 
• A mission that matters in an industry going through its biggest transformation in a century.  
• A team worth working with — big hustle, low ego, great vibes — that’s motivated by solving difficult, meaningful problems. 
• All-expenses-paid trips to Australia to co-work with your colleagues ‘down under.’ 
• Flexible, hybrid working environment with offices in San Francisco and Austin.