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# AI Data Engineer 3

- **Company:** Propertyvalue Team Red Dog
- **Location:** Redmond, United States (Remote available)
- **Experience:** Expert
- **Salary:** $135,200.0 - $156,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Business Analytics Applications, Data Analysis, Big Data, Information Systems, Databases, Computer Engineering, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Relational Databases, Database Schema, Python (Programming Language), Cloud Services, Shell Script, SQL Databases, Workflow Management Systems, Enterprise Data Management, Scripting, Cloud Platform System, Software Troubleshooting, Semi-structured Data, Information Technology, Data Analytics, Integration Frameworks, Data Management, Tools for Reporting, Data Pipelines
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/17a5a0e5-a6b9-4fa9-81d6-dd9ee1041ab3

## About the Role

1. SQL and Relational Database Development - Strong experience designing, optimizing, and maintaining relational databases, schemas, and enterprise-scale data models to support analytics and reporting solutions.
 2. ETL/ELT Pipeline Development and Data Integration - Proven ability to build, automate, and support scalable ETL/ELT workflows that ingest, transform, validate, and deliver analytics-ready datasets across multiple enterprise systems.
 3. Python or Shell Scripting - Hands-on scripting experience used for automation, workflow orchestration, data transformation, monitoring, and troubleshooting of enterprise data pipelines.
 4. Cloud Data Platforms and Enterprise Data Engineering - Experience working with modern cloud-based data environments and enterprise data infrastructure to improve scalability, reliability, governance, and accessibility., Bachelor's degree in Computer Science, Computer Engineering, Information Systems, or related technical field required
5-7 years of experience in data engineering, ETL development, database engineering, analytics engineering, or related technical work
Strong experience with relational databases and database technologies
Experience building and maintaining ETL/ELT pipelines and enterprise data integration workflows
Proficiency in SQL and at least one scripting/programming language such as Python or Shell scripting
Experience working with cloud-based data platforms and modern data environments preferred
Strong troubleshooting, analytical, and problem-solving abilities
Strong written and verbal communication skills with the ability to collaborate cross-functionally
Experience supporting enterprise-scale databases, cloud platforms, and data integration tools preferred
Demonstrated success supporting data-driven business initiatives and analytics solutions

What makes a candidate highly successful in this role:

Successful candidates are highly analytical, proactive, and capable of managing complex enterprise data workflows with minimal oversight. They bring strong technical depth in SQL, ETL/ELT development, cloud data platforms, and scripting while also demonstrating excellent communication and collaboration skills across technical and business teams. Candidates who stand out typically have experience improving data quality, optimizing large-scale data systems, automating processes, and delivering scalable analytics-ready solutions in fast-paced enterprise environments.

## Description

This role offers the opportunity to work on large-scale enterprise data initiatives that support analytics, reporting, AI/ML programs, and business intelligence across a modern technology environment. The AI Data Engineer will play a key role in modernizing data infrastructure, improving data quality and accessibility, and building scalable solutions that enable business teams to make informed, data-driven decisions. This position provides exposure to enterprise cloud technologies, cross-functional collaboration, and impactful data engineering projects supporting long-term innovation initiatives.

How you will make an impact:
Collaborate with technical teams, analysts, and business stakeholders to gather requirements and support enterprise data initiatives
Design, develop, automate, and maintain scalable ETL/ELT pipelines and enterprise data workflows
Build and optimize logical and physical database structures, schemas, and data models
Support ingestion, transformation, cleansing, and validation of structured and semi-structured data from multiple sources
Troubleshoot and resolve data quality, pipeline performance, and integration issues across enterprise systems
Modify and enhance existing databases, ETL processes, and data management systems to improve scalability and reliability
Perform testing, validation, and monitoring of data pipelines and database systems to ensure data accuracy and integrity
Create and maintain technical documentation related to data pipelines, database objects, workflows, and processes
Partner with data analysts, engineers, and data scientists to provide clean, reliable, and analytics-ready datasets
Support implementation of best practices for data governance, security, and process optimization


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