Data Engineer, AI Enablement

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 Follow @abbvie onLinkedIn,Facebook,Instagram,XandYouTube. 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 Follow @abbvie onLinkedIn,Facebook,Instagram,XandYouTube. Job Description AbbVies Business Technology Solutions (BTS) Information Research (IR) organizationis seekingaData Engineer, AI Enablementto help deliver trusted, well-structured, AI-ready data products within ARCH, AbbVies R&D Convergence Hub. As part ofthe DELOSteam 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, develop, andoperate scalable data pipelines and curated data products that make high-value research data easier to find, connect, understand, and use. The work spans data curation, normalization, modeling, metadata, lineage, quality controls, governance, documentation, and publication to the ARCH knowledge graph. Rather than developing AI models directly, you will ensure that data science, AI engineering, and research partners have the reliable, accessible, and appropriately governed data they need to deliver trusted outcomes. Working closely with R&D stakeholders, data scientists, machine learning engineers, platform teams, architects, and data owners, you will help translate scientific and business needs into dependable data solutions. You will also help scale delivery by providing technical guidance to contracted engineers supporting the same data products, translating requirements into clear work, reviewing outputs, helping remove barriers, and ensuring results meet agreed quality, documentation, and acceptance standards. Under the direction of theAssociate DirectorData Strategy, AI & Knowledge Enablement, thisrole is an opportunity to contribute at the center of AbbViesR&D datatransformation. The data foundationsyou build will helpdeterminewhich analytics, knowledgegraph, and AI use cases are possible across research and howconfidentlythe organization canusetheir outputto support scientific decision-making. Responsibilities AI-Ready Data Product Engineering:Design, build, andoperatecurated, reusable data products that make high-value R&D data easier to find, connect, understand, and use. Collect, integrate, normalize, model, and transform data from databases, applications, APIs, licensed external sources, and other systems into ARCH and related data environments. Trusted Data Foundation Enablement:Establishreliable, scalable data foundations that support analytics, reporting, knowledge graph capabilities, machine learning, and AI-enabled use cases. Ensure data assets are structured, documented, accessible, governed, traceable, and fit for downstream consumption. AI, RAG & Knowledge Graph Readiness:Prepare data and documents for AI and knowledge discovery use cases by cleaning, standardizing, enriching, labeling, organizing metadata, supportingchunking, and embedding workflows, and producing vector database-ready assets. Enable publication of curated data to the ARCH knowledge graph. Data Quality, Governance & Documentation:Apply data quality and governance practices, including accuracy and completeness checks, metadata, lineage, access controls, privacy, license terms, assumptions, quality rules, and appropriate-use guidance so data consumers can understand and trust the assets they use. Technical Coordination & Delivery Support:Collaborate with data scientists, machine learning engineers, software engineers, platform teams, architects, data owners, and R&D stakeholders to translate scientific and business requirements into usable AI-ready data products.Providetechnical guidance tocontractedengineers, clarify work, review outputs,helpremove barriers, andsupportdeliveryagainstagreed quality and acceptance standards. Operational Reliability & Continuous Improvement:Monitor pipeline performance, data freshness, cost, failures, and delivery issues; troubleshoot andresolve problems before theyimpactdata consumers. Contribute to reusable engineering patterns, automation, process improvements, and consistent ways of working across data product workflows. Compliance & Standards:Follow applicable Corporate and Divisional policies, includingGxPcompliance, data security, software development lifecycle practices, data governance standards, and relevant regulatory or contractual requirements. Qualifications Required Bachelors Degree with 5 years of experience; ORMastersDegree with 4 years of experience in information technology, data engineering, data management, analytics, life sciences, ora relatedfield. Hands-on experience designing, developing, andoperatingproduction data pipelinesandcurateddata productsusingSQL, Python, ETL/ELT patterns, and workflow orchestrationtoolssuch as Airflow. Working knowledge of modern data platforms, data integration, data warehousing orlakehousepatterns, distributed SQL or big data environments, cloudinfrastructure,andanalytics enablement. Experience preparing data fordownstream analytics, machine learning, knowledgegraph, or retrieval use cases, including cleaning,standardization, enrichment,structuring, metadata organization, and support for embedding or vector-search workflows. Experience applying data quality, metadata management, governance, lineage, documentation, and data modeling practices to support trusted, reusable data products. Experience collaborating with cross-functional business, scientific, technical, platform, vendor, contractor, or managed-services teams to translate requirementsand deliver fit-for-purpose data assets. Ability tooperatewith a high degree of autonomy, manage priorities across concurrent workstreams,modifyapproach when needed, escalopen issues, and keep stakeholders informed through clear written and verbal communication. Demonstrated ability to learn, understand, andapplynewdata engineering, platform,andAI-enablementtechnologies, and toserveas atechnicalresourcefor others. Experienceproviding technicalinput, clarifyingrequirements,and reviewingoutputs fromcontracted, vendor, or managed-services engineers without direct reporting authority. Strong communication, planning, and organizational skills, with the ability toexplaintechnicalconceptsandkeepstakeholdersinformed. Dataproduct engineeringmindset, with the ability toshapereusable, well-structured data assets thatare practical, scalable, and fit foranalyticsand AI-enabled use. Data curation and stewardship mindset, with attention toquality, metadata,lineage, governance, standards,documentation,andappropriate use. Technical fluencyacrossdata platforms, pipelines, integration patterns, orchestration,cloudenvironments,anddata delivery practicessufficient to work effectively with engineering and platform teams. Operational discipline acrossmonitoring, troubleshootingprioritization,issue resolution,automation,reusablepatterns,and continuous improvement. Technical coordination and influence, with the ability to clarifypriorities, guide work, review outputs,resolve ambiguity, and coordinate across internalandexternal contributors. Stakeholder communication, with the ability toframe tradeoffs, risks, dependencies, andprogress in a clear and practical wayfor technical, scientific, and business audiences. Preferred Pharmaceutical or healthcare industry experience preferred. Experience supporting research, discovery, translational, clinical, scientific, or other life sciences data environments. Familiarity with graph databases, knowledge graphs, ontology-based data structures, semantic data, metadata-driven data products, orlinked-dataconcepts. Experience working with AWS-based, cloud-based,lakehouse, or modern data platform technologies such as Databricks, Spark, Snowflake, Neo4j, or similar tools. Experience working with regulated data environments, including data governance, documentation, security, privacy, license terms, or compliance expectations. Exposure toanalytics, machine learning, retrieval-augmented generation (RAG), embeddings, vector databases, AI-search patterns, or AI-ready data product delivery. Familiarity with Agile practices or planning tools such as Jira, including backlog refinement, sprint planning, prioritization, acceptance criteria, and delivery tracking. Additional Information The compensation range described below is the range of possible base pay compensation that the Company believes ingood faith it will pay for this role at thetimeofthis posting based on the job grade for this position.Individualcompensation paid within this range will depend on many factors including geographiclocation,andwemayultimatelypaymore or less than the posted range. This range may bemodifiedin thefuture. We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick),medical/dental/visioninsurance and 401(k) to eligibleemployees. This job is eligible toparticipatein our short-term incentiveprograms. 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 US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more: #J-18808-Ljbffr BioSpace, Inc.