Principal Data Engineer, AI Enablement

AbbVie

Confirmed live today High trust

Quick summary

Work type: On-site
Location: North Chicago, IL
Salary: $124,500–$236,500 / yr
Posted: 4 days ago
Freshness: Confirmed live today
Closes: Oct 7, 2126
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $186k

This role $180k

$111k $250k

below market most similar roles pay here above market

This role pays less than 51% of similar roles. Most pay $149,106–$221,925 — the blue band above. At the midpoint, this role pays about $180k versus about $186k for comparable roles.

Based on 240 similar postings.

Employer

About AbbVie

AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.

AbbVie currently has 158 open roles on FindRole.

Listed pay typically runs $109,500–$208,500 across 148 roles with salary data.

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At a glance

TL;DR · Principal Data Engineer, AI Enablement

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The Principal Data Engineer, AI Enablement joins a cross-functional team to design, develop, and maintain scalable data solutions that drive AI and machine learning use cases. This role involves collaborating with data scientists and architects to deliver fit-for-purpose solutions for the pharma value chain. Key responsibilities include integrating LLMs like GPT or Claude for data mining, operationalizing machine learning models through lifecycle management, and creating expressive data models for graph analytics and semantic reasoning. The position requires expertise in MLOps, Data Agents, Agentic Memory, Graph RAG systems, and unstructured data processing. Candidates must be proficient in Python, SQL, and Spark, with experience in ETL/ELT processes and CI/CD. Preferred skills include Neo4j, Elasticsearch, and AWS to support emerging technologies in the AI data space.

What does a Data Engineer earn?

Median $159125 from 199 postings across 61 companies.

See salary data

Skills

Python SQL Spark MLOps LLM Graph RAG ETL ELT AWS Neo4j Elasticsearch CI/CD Vector Stores text mining GenAI

What you'll do

Design, develop, and maintain scalable AI-ready data solutions for diverse pharmaceutical data sets.
Integrate Large Language Models (LLMs) for data mining, knowledge extraction, and automated insights.
Operationalize machine learning models by managing deployment, monitoring, and the full model lifecycle.
Translate user requirements into data models that support graph analytics, semantic reasoning, and GenAI.
Research and recommend tools for graph databases, vector stores, and agent-based solutions.
Provide technical leadership and subject matter expertise on emerging technologies in the AI data space.
Ensure all data solutions comply with corporate software development, lifecycle policies, and security procedures.

What we're looking for

Bachelor's Degree with 8 years of experience, Master's Degree with 7 years, or PhD with 3 years of related work experience.
Experience with MLOps, LLM integration, Data Agents, Agentic Memory, Graph RAG systems, text mining, and unstructured data processing.
Experience designing and building data pipelines, ETL/ELT processes, and data models.
Proficiency with Python, SQL, and distributed data processing frameworks such as Spark.
Experience with CI/CD practices, data quality controls, governance, and security considerations.
Degree in Computer Science or related discipline (preferred); advanced degree (preferred).
Experience with Neo4j and Elasticsearch database technologies (preferred).
AWS experience (preferred).

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