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Forward-Deployed Data EngineerGRIDSIGHT • Austin, Texas, United States
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Forward-Deployed Data Engineer

GRIDSIGHT
  • US
    Austin, Texas, United States
  • US
    Austin, Texas, United States
Postuler Maintenant

À propos

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 utility deployments underway and a strong pipeline behind them. 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 sales, product, and solutions engineering — close to customers, close to the commercial team, and close to the product decisions that shape what we build next. If you're someone who wants to see the full picture of a fast-scaling company rather than execute in a narrow lane, this is that role. The Role As a Forward Deployed Data Engineer at Gridsight, you will own the full arc of customer data engagement. 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. Alongside implementation work, you'll deliver bespoke analytics that answer the questions customers can't yet answer themselves. You’ll also contribute to the internal tooling that makes the next implementation faster and to the product work that accelerates time-to-value. 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. This is a rare role: equal parts customer partner, data engineer, and analyst. You'll be at the forefront of how Gridsight transforms the largest electric utilities in the world. Key Responsibilities Customer Implementations (~50%) 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. Debug integration issues with composure — triaging problems, communicating clearly with customers, and driving resolution. Run and monitor the data pipelines required to deliver a successful implementation. Analytics (~40%) Work with customers to translate business questions into analytical tasks, and communicate findings clearly to both technical and non-technical audiences. Deliver ad hoc and bespoke analysis for customers — answering operational questions, investigating anomalies, and surfacing insights that aren't yet available through the product. Product Support (~10%) 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. 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. Qualifications 5+ 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. What We Offer Rapidly scaling venture-backed company on the ground floor. Highly competitive salary, equity, and benefits package including wellness and home-office stipends, healthcare, 401K, and parental leave. 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 hard problems. Free annual trips to Australia to co-work with your colleagues ‘down under.’ Flexible, hybrid working environment with offices in San Francisco and Austin.
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  • Austin, Texas, United States

Compétences linguistiques

  • English
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