Engineer, Technology I

Job Description

AbbVie’s Business Technology Solutions (BTS) Information Research (IR) organization is seeking an Engineer, Technology I to help deliver trusted, well-structured, AI-ready data products within ARCH, AbbVie’s R&D Convergence Hub. As part of the DELOS team — Data Exploration and Linked Outcome Solutions — this role helps build the reliable data foundations needed to advance analytics, reporting, knowledge graph capabilities, machine learning, and AI-enabled use cases across R&D.

In this role, you will independently design and develop data pipelines and curated data assets within assigned projects, applying established architecture, engineering patterns, and governance standards. You will collect, integrate, normalize, model, and document research data; implement quality checks; and support publication to the ARCH knowledge graph. Rather than developing AI models directly, you will prepare reliable, accessible, and appropriately governed data for analytics, data science, and AI-enabled use cases.

Working with R&D stakeholders, data scientists, machine learning engineers, platform teams, architects, and data owners, you will translate defined scientific and business requirements into dependable data solutions. You will perform routine and complex engineering tasks independently, understand project objectives and your contribution to them, adapt your approach when needed, and communicate progress, risks, and issues. You will collaborate with internal and contracted engineers on assigned work, seeking guidance on broader architecture decisions and escalating issues outside your scope.

Under the direction of the Associate Director – Data Strategy, AI & Knowledge Enablement, this role contributes to AbbVie’s R&D data transformation by delivering consistent, well-documented data solutions within agreed project scope and timelines. You will learn and apply new methods and technologies to help research partners use trusted data for scientific decision-making.

**This is a hybrid role based in Lake County, IL (Tue, Wed, Thu)

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. Understand broader project objectives, organize assigned work, and adapt your approach when requirements or priorities change.
• AI & Knowledge Graph Data Preparation: Clean, standardize, enrich, and structure data and documents for downstream analytics, machine learning, retrieval-augmented generation (RAG), and knowledge discovery. Organize metadata, support established chunking and embedding workflows, and prepare curated assets for publication to the ARCH knowledge graph.
• Data Quality & Technical Documentation: Implement defined data quality checks and maintain technical documentation for pipelines and data assets, including metadata, lineage, transformations, assumptions, and usage guidance. Apply established access, privacy, licensing, and governance requirements.
• Collaboration & Progress Communication: Work with scientific, business, engineering, and platform partners to clarify requirements and deliver assigned work. Clearly present project objectives, progress, risks, and issues; collaborate with internal and contracted contributors without responsibility for directing their delivery.
• Operations & Method Improvement: Monitor assigned pipelines for performance, freshness, failures, and resource use; troubleshoot and resolve issues within your scope and escalate when needed. Learn and implement new methods and technologies and contribute to reusable patterns and automation with guidance as appropriate.
• Compliance & Standards: Understand and adhere to applicable Corporate and Divisional policies, including code of conduct, safety, GxP compliance, data security, data governance, relevant regulatory or contractual requirements, and the software development lifecycle.

Qualifications

• Bachelor’s Degree in Information Technology, Data Engineering, Computer Science, Informatics, Life Sciences, or a related field plus 4 years of experience; Master’s Degree plus 2 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.

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