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# Database Engineer

- **Company:** TRUE BLUE INC
- **Location:** United States (Remote available)
- **Salary:** $80,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Data Analysis, Big Data, Databases, Data Infrastructure, Extract Transform Load (ETL), Instant Messaging Technology, Python (Programming Language), PostgreSQL, Standard Sql, SQL Databases, Twilio, Database Performance
- **Published:** July 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=54f76cd5c8acfec1

## About the Role

The ideal candidate has experience building large scale data systems, experience in Democratic politics, and experience with large scale texting platforms (Switchboard, Scale to Win, Twilio). While an ideal candidate will have all the experience mentioned, most candidates will have a mix of different experiences and are encouraged to apply., * Professional experience with PostgreSQL, AWS, and APIs.

 * Strong SQL and Python skills.
 * Experience working with large, complex datasets.
 * Strong problem-solving skills and attention to detail.
 * Ability to be self-directed.

## Description

True Blue Analytics is seeking a Database Engineer to build and maintain the data infrastructure that will power an emerging analytics product. This role focuses on designing scalable database systems, developing reliable ETL pipelines that can handle scale, and processing large volumes of client data efficiently and accurately.

The Database Engineer will be expected to communicate professionally and clearly with other technical staff, client-facing staff, and managers. You will work closely with analytics, and client-facing team members to ensure data is securely ingested, transformed, validated, and delivered for downstream analytics and reporting. This is a hands-on role with a focus on technical systems and automation., * Design, build, and maintain PostgreSQL databases that support large-scale data processing.

 * Develop and maintain pipelines for ingesting, validating, transforming, and exporting datasets.
 * Optimize SQL queries and database performance for large datasets.
 * Build Python tools and automation to streamline recurring data workflows.
 * Collaborate with client-facing and analytics team members to support new data products and workflows.


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