AI-Ready Data Engineer I (Hybrid)

AbbVie Inc.

Mettawa (IL)

Hybrid

USD 75,000 - 143,000

Full time

30 hours ago
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Job summary

AbbVie Inc. in Lake County, IL, is seeking an Engineer, Technology I to help deliver AI-ready data products within ARCH, AbbVie’s R&D Convergence Hub.

You will design and develop data pipelines, collect, normalize, model, and document research data, and prepare data for analytics and AI use cases. You will collaborate with data scientists, researchers, and platform teams, ensuring data quality, governance, and timely delivery while adhering to compliance standards.

Qualifications

  • Bachelor’s Degree in Information Technology, Data Engineering, Computer Science, Informatics, Life Sciences, or a related field plus 4 years of experience.
  • Practical experience developing data pipelines or data solutions using SQL, Python, and ETL/ELT patterns, with knowledge of workflow orchestration tools such as Airflow.
  • Theoretical and practical knowledge of data integration, data modeling, data storage, and modern data platforms sufficient to independently complete routine and complex engineering tasks within established standards.
  • Experience cleaning, standardizing, transforming, and documenting data for analytics or scientific use, including applying data quality checks and organizing metadata.
  • Ability to organize assigned work, multitask, meet timelines, understand project objectives, adapt your approach when needed, and learn and apply new methods and technologies.
  • Strong written and oral English communication skills, with the ability to explain technical work, present project objectives and progress, and collaborate with scientific, business, and technical partners.
  • Hands-on data engineering: develop reusable, well-structured data assets for defined analytics and AI-enabled use cases.
  • Data quality and documentation: apply established metadata, lineage, governance, and appropriate-use practices to assigned data assets.
  • Technical problem-solving: apply practical knowledge of data platforms, pipelines, integration, and orchestration; learn and implement new tools and methods.
  • Work planning and operational discipline: organize concurrent assignments, monitor pipelines, troubleshoot issues, meet timelines, and elevate risks when needed.
  • Team collaboration: clarify requirements, share technical knowledge, and work effectively with internal and external contributors on assigned project tasks.
  • Clear communication: explain technical concepts and present project objectives, progress, risks, and dependencies to scientific, business, and technical audiences.

Responsibilities

  • Data Pipeline & Product Development: Independently design and develop pipelines and curated data assets for assigned scientific or business use cases.
  • Collect, integrate, normalize, model, and transform data from databases, applications, APIs, licensed external sources, and other systems using established engineering patterns.
  • Reliable Project Delivery: Perform routine and complex engineering tasks competently and independently, producing reliable and consistent results within agreed timelines.
  • AI & Knowledge Graph Data Preparation: Clean, standardize, enrich, and structure data and documents for downstream analytics, ML, RAG, and knowledge discovery.
  • Data Quality & Technical Documentation: Implement defined data quality checks and maintain technical documentation for pipelines and data assets.

Skills

SQL
Python
Data pipelines
English communication

Education

Bachelor’s Degree in Information Technology, Data Engineering, Computer Science, Informatics, Life Sciences

Tools

Airflow

Job description

AbbVie Inc. in Lake County, IL, is seeking an Engineer, Technology I to help deliver AI-ready data products within ARCH, AbbVie’s R&D Convergence Hub.

You will design and develop data pipelines, collect, normalize, model, and document research data, and prepare data for analytics and AI use cases. You will collaborate with data scientists, researchers, and platform teams, ensuring data quality, governance, and timely delivery while adhering to compliance standards.

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