Customer Data Engineering Lead

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 a vertical AI platform that enables electric utilities to modernize grid operations, accelerate interconnection, and unlock dynamic grid capacity. The opportunity is enormous. We're embedded with over 50% of Australia's distribution networks and working with multiple top 10 utilities in the US. We just closed our Series B led by Insight Partners and Galvanize Climate, and we're on the path to build a truly generational utility software company. We are a team of builders. What unites us is that we’re curious, hungry and obsessed with maximizing the impact we can deliver to Gridsight and the energy transition. If that sounds like you, come join us!

About the role You will lead customer data engineering for Gridsight's US customers, owning the team, its resourcing and the successful delivery of customer data into the platform. Beyond day-to-day delivery, you will be responsible for building a high-performing team and continuously improving how we implement customers. This means simplifying processes, introducing automation and building the standards, tooling and capabilities needed to deliver implementations faster, more reliably and at scale. You will work closely with Product, Power Engineering, Customer Success, Data Platform and Commercial to ensure customer commitments are realistic, implementation challenges are resolved and what we learn from each implementation makes the next one better. You are accountable for every US customer data implementation landing on time, at quality, with the customer confident in the result.

Key Responsibilities Delivery

• Own CDE delivery for US customers: including Platform Stand Ups, Refreshes, Integration Changes, and the BAU work around them (data bug fixes, incidents and investigations).
• Own the implementation process, with clear exit criteria at each stage.
• Be the escalation point when a customer's data is late, wrong or blocked, and keep SLA conversations honest about who has the ball.
• Make realistic commitments on dates and scope in partnership with the US power engineering and commercial team before they reach the customer.

Resourcing and coordination

• Own the US allocation on the CDE Weekly Schedule: who works on which customer, week by week.
• Forecast capacity against the pipeline of signed and expected customers, and make the case for hiring when the numbers say so.
• Keep Linear as the honest record of the work, following CDE conventions, so anyone can see status without asking.

People and capability

• Lead, hire, coach and performance-manage the US customer data engineers.
• Lift the whole team's skills: SQL and data modelling depth, utility data domain knowledge, and judgement with ambiguous customers.
• Run a clear growth progression for new CDE’s (Customer Data Engineers)
• Work as one team with the ANZ and UK: shared standards, written handovers and rotating walkthroughs across time zones.
• Onboard new CDE team members.

Alignment across teams

• Be the bridge between CDE, Product and Data Platform so all three are pulling in the same direction.
• Turn what the team learns in implementations into clear requirements across product, data platform and operations teams.
• Make sure the CDE team has the tooling, access, environments and documentation it needs before each implementation starts.

Continuous improvement of the team, process and its automation You will own how the team's way of working gets better over time, the automation that drives it, and take the lead on anything that falls outside our standard pipelines. The goal is that every implementation is faster and more predictable than the last.

• Own the end-to-end implementation process.
• Map the process as it actually runs today: every step, handoff and decision point, and where effort and elapsed time go.
• Define what good looks like at each stage: standards, exit criteria, templates and the quality bar the team works to.
• Fix the process before you automate it. Remove steps that don’t add value and simplify handoffs with Product, Data Platform and the customer.
• Automate the improved process step by step: reusable data checks run at each stage, sample-data analysis, mapping assistance, runbooks and agent skills.
• Keep the process documented and current, so new CDEs can follow it and everyone works the same way across regions.
• Measure the impact of these changes.

New and bespoke data sources

• Lead the team in defining and maintaining data requirements for each product, keeping them clear, current and consistent across customers.
• Make sure the team manages customer exceptions to those requirements, and that they are agreed and recorded.
• Guide the team in bridging what the platform needs and what each customer can realistically provide.
• Lead agreeing data plans with internal teams and the customer before work starts, and to meeting quality gates before work moves on.
• Make sure US CDE is represented early in new products and new implementations, so scope and timelines are realistic.

What you'll bring

• 6+ years in data engineering or technical implementation, including 2+ years leading a team or owning delivery across multiple customers.
• Strong SQL, DBT and Python, with the depth to review a mapping or transformation and spot what’s wrong with a customer’s data.
• Hands-on experience building and running data pipelines, from ingestion and orchestration to validation, in a git-based workflow.
• A track record of delivering customer data implementations to committed dates, including handling escalations when data is late, wrong or blocked.
• Process ownership: you’ve defined stage gates, standards and runbooks, simplified them, then automated and measured the result.
• Experience hiring, coaching, and performance-managing engineers.
• Comfort with ambiguity, bridging what a platform needs and what a customer can realistically provide.
• Clear, written-first communication that works across Product, Power Engineering, Commercial and teams in other time zones.

What would set you apart

• Experience with electricity utility data such as network GIS, AMI, SCADA telemetry or DER registers.
• Familiarity with US utilities and their data systems.
• Experience using AI agents or automation to speed up data work, such as reusable data checks or mapping assistance.
• Experience building a team and its playbook at the same time in a fast-growing startup.

What we offer

• 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.
• Hybrid work environment from our offices in San Francisco, CA and Austin, Texas, plus annual retreats to the Australian mothership.

Gridsight is an equal opportunity employer committed to fostering a diverse and inclusive workplace. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by applicable federal, state, or local laws. All employment decisions are made based on qualifications, merit, and business needs. We encourage all qualified candidates to apply and join our team.