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# Data Engineer

- **Company:** Brighton, Inc.
- **Location:** City of Industry, CA, United States
- **Experience:** Experienced
- **Salary:** $90,000.0 - $120,000.0
- **Contract:** Permanent contract
- **Skills:** JavaScript (Programming Language), .NET Framework, PHP (Programming Language), Microsoft Excel, Software as a Service, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Database Queries, Python (Programming Language), Pivot Tables, SQL Databases, Tableau (Software), Web Analytics, Scripting, Looker Analytics, Data Pipelines
- **Published:** July 2, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f8cab4de62596853

## About the Role

You will bring technical depth across SaaS ETL, data warehouses, SQL, Python, and Excel/Google Sheets, and you will use those skills to connect data across our business, surface meaningful patterns, and support decision-making at every level. Your attention to detail matters here, as does your ability to work collaboratively with stakeholders who have different goals and levels of technical fluency., * You understand that the end goal of data is better customer engagement

 * You have a relentless but practical drive to make data accurate, immediate, and available
 * You dig into root problems before proposing solutions, and follow through once you do
 * You can hold multiple priorities and deadlines without dropping the ball

You should have

 * 4-5 years in a data-focused or technical role
 * Strong SQL skills (any variant)
 * Proficiency in Python, JavaScript, PHP, or .NET
 * Experience building and maintaining data pipelines
 * Expert-level Excel (pivot tables, vlookups, etc.)
 * Clear communicator with both technical and non-technical audiences
 * Self-starter who can manage priorities and workload with minimal supervision
 * Familiarity with BI/dashboarding tools a plus (Looker, Sigma, Tableau, Metabase, etc.)
 * Naturally curious and motivated to answer questions with data

## Description

* Build, test, and deploy ETL/ELT patterns in an efficient, organized manner
 * Own data acquisition, transformation, modeling, and lineage
 * Manage data pipelines using DAG tools, SaaS ELT, and custom scripts
 * Partner with tech, marketing, and field teams to build scalable solutions that improve data accuracy, immediacy, and availability
 * Go beyond data engineering when needed: support the team with advertising performance, website analytics, customer segmentation, ROI modeling, LTV analysis, cross-channel analysis, media mix, and survey design
 * Communicate findings clearly to both technical and non-technical stakeholders


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