Customer Data Engineer — Hybrid, Global Impact, Australia Trips

Gridsight; San Francisco (CA); Hybrid; USD 130,000 - 190,000; Full time

Benefits offered by this job

Equity

Benefits

Trips to Australia

Hybrid work

Job summary

Gridsight in San Francisco is seeking a Customer Data Engineer to own data integration with utility customers and accelerate value from our AI-powered platform. You’ll work directly with customers to understand data environments, guide them through requirements, and lead the data ingestion into the platform.

You’ll split time between customer conversations and hands-on data wrangling, building pipelines, and contributing to internal tooling to speed future implementations, with hybrid work

Qualifications

• 4+ years of professional experience in data engineering or analytics with customer engagement.
• Advanced SQL skills and ability to analyze and wrangle complex datasets.
• Proficiency in Python for data transformation and scripting.
• Experience with dbt or similar ELT/ETL frameworks.
• Ability to lead customer-facing technical engagements and drive deliveries.

Responsibilities

• Lead end-to-end data implementation engagements with utility customers.
• Set up and configure data infrastructure per current implementation process.
• Map incoming customer data to Gridsight schemas and develop data transformations.
• Review data quality and provide clear feedback on issues.
• Run and monitor data pipelines to deliver successful implementations.
• Collaborate with product and data engineering to build reusable tooling.

Job description

Gridsight in San Francisco is seeking a Customer Data Engineer to own data integration with utility customers and accelerate value from our AI-powered platform. You’ll work directly with customers to understand data environments, guide them through requirements, and lead the data ingestion into the platform.

You’ll split time between customer conversations and hands-on data wrangling, building pipelines, and contributing to internal tooling to speed future implementations, with hybrid work