AI Data Engineer 3

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

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.

At Team Red Dog, people are at the heart of everything we do. Our commitment to personalized service and our deep experience in matching talented professionals with meaningful roles at some of the world’s most inspiring companies is what sets us apart. We take the time to understand your unique skills, strengths, and passions-because we believe your career should reflect who you are.

Whether you’re looking to grow, pivot, or simply find a place where your work truly matters, we offer opportunities that empower you to make a positive impact. With excellent benefits, a supportive team, and a role where you can thrive while doing what you love, we’re here to help you take the next step with confidence. Join us-and discover what it means to be genuinely valued in your career.

Generous benefits package for qualified employees includes: Health insurance (medical, dental, vision, and life) Employer-matched 401K plan Paid time off Paid holidays, We offer competitive compensation aligned with U.S. industry standards, and our final offer will reflect the candidate’s location, job-specific skills, experience, and knowledge. All applicants must be authorized to work in the U.S. without the need for sponsorship. Team Red Dog is an E-Verify employer. Employment is contingent upon the successful completion of a reference and background check. Please no solicitations from C2C or recruiting firms.

Team Red Dog is building a pipeline of qualified candidates for an anticipated AI Data Engineer 3 opening with one of our long-term enterprise technology clients. This opportunity is expected to focus on enterprise data engineering, cloud-based analytics infrastructure, ETL/ELT development, and AI/ML-driven data initiatives supporting large-scale business operations. This role will help design and optimize scalable data platforms that power reporting, analytics, automation, and enterprise decision-making across complex environments. The ideal candidate will bring strong expertise in SQL, modern data integration, and cloud data engineering while collaborating cross-functionally with engineers, analysts, and business stakeholders to deliver reliable, analytics-ready solutions.