Engineer, Technology I

Posted 2 Days Ago
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North Chicago, IL, USA
Hybrid
75K-143K Annually
Mid level
Healthtech • Pharmaceutical
The Role
Develop data pipelines and curated data assets for scientific and business use cases. Integrate, normalize, model, document, and quality-check data for analytics, machine learning, retrieval-augmented generation, and knowledge graph publication. Monitor pipeline performance, troubleshoot issues, apply governance and compliance standards, and collaborate with scientific, business, engineering, and platform teams.
Summary Generated by Built In
Company Description

About AbbVie

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

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.
  • 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 escalate 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.

Preferred

  • Pharmaceutical, healthcare, or life sciences industry experience, particularly with research, discovery, translational, clinical, or scientific data.
  • Familiarity with knowledge graphs, graph databases, ontology-based structures, semantic data, or linked-data concepts.
  • Exposure to cloud or modern data platform technologies such as AWS, Databricks, Spark, Snowflake, or Neo4j, and to Agile delivery practices or tools such as Jira.
  • Exposure to data preparation for machine learning, retrieval-augmented generation (RAG), embeddings, or vector search, and familiarity with governance, security, privacy, licensing, or documentation in regulated data environments.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

  • The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at  the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors  including  geographic location, and we may ultimately  pay more or less than the posted range. This range may be  modified in the future. ​

  • We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.​

  • This job is eligible to  participate in our short-term incentive programs.  ​

Note: No amount of pay is  considered to be wages or compensation until such amount is earned,  vested,  and determinable. The amount and availability of  any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a   particular employee  remains in the Company's sole and absolute discretion unless and until paid and may be  modified at the Company’s sole and absolute discretion,  consistent with applicable law. ​

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community.  Equal Opportunity Employer/Veterans/Disabled. 

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

Skills Required

  • Bachelor's degree in Information Technology, Data Engineering, Computer Science, Informatics, Life Sciences, or a related field plus 4 years of experience
  • Alternatively, a Master's degree plus 2 years of experience
  • Experience developing data pipelines or data solutions using SQL, Python, and ETL or ELT patterns
  • Knowledge of workflow orchestration tools such as Airflow
  • Knowledge of data integration, data modeling, data storage, and modern data platforms
  • Experience cleaning, standardizing, transforming, and documenting data for analytics or scientific use
  • Experience applying data quality checks and organizing metadata
  • Ability to organize work, multitask, meet timelines, adapt to changing priorities, and learn new technologies
  • Strong written and oral English communication skills
  • Experience developing reusable data assets for analytics and AI-enabled use cases
  • Ability to apply metadata, lineage, governance, and appropriate-use practices
  • Ability to troubleshoot data platforms, pipelines, integration, and orchestration issues
  • Ability to collaborate with internal and external contributors
  • Pharmaceutical, healthcare, or life sciences industry experience
  • Familiarity with knowledge graphs, graph databases, ontologies, semantic data, or linked-data concepts
  • Exposure to AWS, Databricks, Spark, Snowflake, or Neo4j
  • Exposure to Agile delivery practices or Jira
  • Exposure to machine learning data preparation, RAG, embeddings, or vector search
  • Familiarity with governance, security, privacy, licensing, or documentation in regulated data environments

AbbVie Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AbbVie and has not been reviewed or approved by AbbVie.

  • Retirement Support — Retirement programs are portrayed as a standout, with a dollar‑for‑dollar 401(k) match up to 6% and an additional annual company contribution based on age and service. Feedback suggests this materially boosts perceived total compensation for many U.S. employees.
  • Parental & Family Support — Paid parental and caregiver leave are emphasized, including up to 12 weeks of fully paid parental leave for all parents and 4 weeks of paid caregiver leave in the U.S. Feedback suggests these policies are a meaningful differentiator for employees balancing family needs.
  • Leave & Time Off Breadth — Time off is described as extensive, with tiered vacation that scales with tenure, 17 company holidays, and two paid volunteer days in the U.S. Feedback suggests the breadth of leave contributes notably to overall benefits satisfaction.

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The Company
HQ: North Chicago, IL
56,000 Employees
Year Founded: 2013

What We Do

AbbVie is a global biopharmaceutical company focused on creating medicines and solutions that put impact first — for patients, communities, and our world. We aim to address complex health issues and enhance people's lives through our core therapeutic areas: immunology, oncology, neuroscience, eye care, aesthetics and other areas of unmet need.

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