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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Customer Data Analyst - **Company:** Gridsight, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Command-Line Interface, Customer Data Management, Information Engineering, Data Infrastructure, Extract Transform Load (ETL), Data Visualization, Database Queries, Software Debugging, Python (Programming Language), Scripting, Git, Data Analytics, Databricks - **Published:** July 18, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=fbf62cd3f365c655 ## About the Role * 2+ years of professional experience in data analytics, analytics engineering, data engineering, technical consulting, or a similar role combining hands-on data work with stakeholder engagement. * Strong SQL skills and demonstrated ability to analyse, validate, and wrangle complex or messy datasets. * Experience building dashboards and data visualizations. * Proficiency in Python for data analysis, transformation, and scripting. * Ability to communicate data-driven findings clearly to both technical and non-technical audiences. * Experience with cloud data infrastructure and modern development practices (Git, command-line environments, collaborative codebases). * Exposure to dbt or similar ELT/ETL frameworks. * Strong problem-solving skills and a methodical approach to troubleshooting technical issues. * Proven problem-solving abilities and a self-starter mentality, comfortable working in a fast-paced startup environment. ## Description As a Customer Data Analyst, you'll turn our utility customers' data into actionable insights. You'll build dashboards and visualizations that help customers see and understand their grid and deliver bespoke analysis that answers questions they can't yet answer themselves. You'll work alongside our Power Engineers, who bring deep subject matter expertise and lead technical delivery with customers. You'll partner with our Customer Data Engineers to make sure the data you need is available, well-structured, and reliable. And you'll work with Product to translate recurring analyses into platform features when we see enough demand across the market. Gridsight runs an AI-forward stack that gives the team 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 great role for someone who loves working with data, enjoys being close to customers, and wants to see their analysis evolve from a one-off deliverable into a product used across the industry., Analytics & Visualization (~55%) * Build dashboards and visualizations for customers, making complex grid data clear and actionable. * Translate customer business questions into analytical tasks, and communicate findings clearly to both technical and non-technical audiences. * Deliver ad hoc and bespoke analysis to answer questions and surface insights that aren't yet available through the product. * Validate outputs against quality standards to ensure analysis is accurate and trustworthy. Customer Delivery Support (~25%) * Work alongside Power Engineers, who provide subject matter expertise and lead technical delivery, to support end-to-end customer engagements. * Partner with Customer Data Engineers to ensure the data required for analytics is available, correctly mapped, and fit for purpose. * Debug data and analysis issues with composure - triaging problems, communicating clearly with customers, and driving resolution. Product Support (~20%) * Identify and communicate patterns across customer engagements to inform product direction. * Partner with Product to translate bespoke analyses into repeatable, platform-ready features where there's enough demand and signal from customers across the market. * Contribute to internal documentation, playbooks, and tooling that improve the efficiency and consistency of future analytics and delivery work. * Bring a tool-first mindset: spot manual steps that can be automated, and take initiative to improve them. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [JavaScript? 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