Principal AI Data Engineer

Job Description

Principal AI Data Engineer

Summary/objective

The Principal AI Data Engineer will lead the development of our modern, intelligent data platform. This role blends deep expertise in data engineering, machine learning infrastructure, and data product development. Will architect and build scalable, cloud-native solutions that enable everything from classic analytics to Retrieval-Augmented Generation (RAG) and advanced feature engineering. The Principal AI Data Engineer should be equally adept at modeling a data warehouse using dbt as optimizing storage for vector embeddings.

Core Job Duties

• Design and implement scalable data models using dimensional modeling and best practices for modern data warehousing.
• Develop and scale dbt transformation pipelines, including testing, documentation, and modularization.
• Architect and optimize Delta Lake / Apache Iceberg tables for high-performance analytics and large-scale ingestion.
• Build production-grade processes in Python, integrating with various data sources & APIs.
• Implement and manage KNN embedding storage (e.g., FAISS, Pinecone, Weaviate, or Azure AI Search) for use in RAG pipelines and ML-powered search or recommendations.
• Establish foundation to support feature engineering, dataset versioning, and model-ready pipelines.
• Enable Retrieval-Augmented Generation (RAG) use cases by building reliable retrieval layers and embedding pipelines to support LLM-based systems.
• Define architecture, development and lifecycle of data products that serve internal users, operational processes, and customer-facing applications.
• Champion cloud-native development practices, primarily on Azure (preferred) including storage, compute, and orchestration tools.
• Establish best practices in CI/CD, observability, testing, governance, and documentation across the data stack.
• Provide technical mentorship and thought leadership across engineering and analytics teams.

Job Complexity

As an expert in the field, uses professional concepts in developing resolution to critical issues and broad design matters. Anticipates broad changes pertaining to their area of expertise and ensure isolved is always ahead of the curve. Significant barriers to entry (e.g., top management review, approval) exist at this level.

Interaction

Works on issues that impact design/selling success or address future concepts, products, or technologies. Creates formal networks with key decision makers and serves as external spokesperson for the organization.

Supervision

Exercises wide latitude in determining objectives and approaches to critical assignments.

Experience

Typically requires a minimum of 15 years of related experience with a Bachelor's degree; or 12 years and a Master's degree; or a PhD in computer science or electronics engineering with 8 years of related experience; or equivalent experience.

Minimum Qualifications

• 8+ years in data engineering or similar technical roles.
• Deep hands-on experience with dbt, SQL, and data warehouse modeling (Kimball, Data Vault, etc.).
• Experience with Apache Iceberg and/or Delta Lake in production-grade systems.
• Expertise in Python and Spark for scalable data processing.
• Experience building and operating KNN/vector databases and embedding stores (e.g., FAISS, Pinecone, Azure AI Search, Weaviate, etc.).
• Familiarity with Retrieval-Augmented Generation (RAG) architecture and implementation best practices.
• Solid understanding of feature engineering workflows and their role in ML and data products.
• Proven ability to build & scale data products that drive insights, decisions, and customer experiences.
• Cloud platform experience, with a strong preference for Azure
• Experience with IaC [Terraform, etc]
• Understanding data governance, privacy, and compliance frameworks (e.g., GDPR, HIPAA, SOC 2).

Nice to Have:

• Familiarity with ML model pipelines (e.g., feature stores, model registries).
• Experience with orchestration tools like Airflow, dbt Cloud, or Azure Data Factory.
• Understanding of modern LLM infrastructure and vector-enhanced applications.
• Desire or experience in Agentic AI
• Experience working in agile product teams or a startup environment.

Physical Demands

Prolonged periods of sitting at a desk and working on a computer. Must be able to lift up to 15 pounds.

Travel Required

Yes, up to 15% domestic travel may be required.

Work Authorization

Employee must be legally authorized to work in the United States.

FLSA Classification

Exempt

Location

Office/Hybrid/Remote

Internal Job Title

Principal AI Data Engineer

About isolved

isolved is an employee experience leader, providing intuitive, people-first HCM (Human Capital Management) technology. Our solutions are delivered directly or through our partner network to more than five million employees and 145,000 employers - who use them every day to boost performance, increase productivity, and accelerate results while reducing risk. Our HCM platform, isolved People Cloud, seamlessly connects and manages the employee journey across talent management, HR & payroll, workforce management and engagement management functions. No matter the industry, we help high-growth organizations employ, enable and empower their workforce by transforming employee experience for a better today and a better tomorrow. For more information, visit www.isolvedhcm.com.

isolved is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. isolved is a progressive and open-minded meritocracy. If you are smart and good at what you do, come as you are. Visit www.isolvedhcm.com/careers for more information regarding our incredible culture and focus on our employee experience. Visit www.isolvedeebenefits.com for a comprehensive list of our employee total rewards offerings.

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