Data Engineer (AI & Data Platforms) - Q126

Job Title: Data Engineer (AI & Data Platforms)

Company: R2 Technologies

Location: Alpharetta, GA (Hybrid / Remote Options Available)

Employment Type: Full-Time / Contractual

About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we have built a reputation as a trusted partner for IT staffing excellence and cutting-edge digital product innovation. We are driven by innovation and operate on a simple philosophy: "We deliver what we promise, and we promise only what we can deliver." Beyond providing top-tier IT talent, R2 builds cutting-edge proprietary solutions like SmartEnt—an Enterprise AI & IoT Intelligence Platform utilizing advanced NLP and AI technologies. By partnering closely with our clients, we deliver technology-driven outcomes that are realistic, measurable, and impactful.

Job Summary: The role of the Data Engineer has fundamentally shifted in 2026. R2 Technologies is seeking an innovative Data Engineer who goes beyond traditional ETL to become a builder of "AI-ready" data foundations. You will be crucial in powering our SmartEnt platform and client AI initiatives by engineering context-rich data pipelines. Utilizing AI coding assistants (GitHub Copilot, Cursor) to automate boilerplate transformations, you will design systems that feed directly into Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures.

Key Responsibilities: * Build and maintain scalable, low-latency data pipelines utilizing modern data stack tools (e.g., dbt, Snowflake, Databricks, Apache Iceberg) to process both structured and unstructured data.

• Integrate and manage Vector Databases (such as Pinecone, Milvus, or Qdrant) to support enterprise semantic search and RAG workflows.

• Leverage AI-assisted coding tools to rapidly generate, test, and optimize SQL/Python data transformation code, freeing up time for complex architectural decisions.

• Orchestrate data workflows using Apache Airflow, Dagster, or n8n to ensure seamless, event-driven data delivery to AI agents and downstream analytics.

• Implement data reliability engineering practices (data contracts, observability, lineage) to ensure LLMs are grounded in highly accurate, governed data.

• Collaborate closely with Full Stack and AI/ML engineers to support multi-modal data ingestion from IoT devices, APIs, and enterprise systems.

Qualifications: 3 years of hands-on experience in Data Engineering, Data Analytics, or ML Engineering.