{"id":963828,"url":"https://alion.io/job/abbvie-data-engineer-ai-enablement","title":"Data Engineer, AI Enablement","company":{"id":3660,"name":"AbbVie","domain":"abbvie.com","url":"https://alion.io/company/abbvie","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":80,"open_postings":68,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chicago, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":84500,"max":162000,"currency":"USD","period":"year","gross":null,"usd_annual":162000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Jira","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Machine Learning","optional":false},{"name":"Neo4j","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-15T19:44:56Z","employer_posted_date":"2026-09-15","last_verified_at":"2026-10-31T04:49:21Z","board_verified":true,"closed_at":null,"days_open":45,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":45},"description":"About AbbVie\nAbbVie'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.\n AbbVie’s Business Technology Solutions (BTS) Information Research (IR) organization is seeking a Data Engineer, AI Enablement 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.\nIn this role, you will independently design, develop, and operate 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.\nWorking 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.\nUnder the direction of the Associate Director - Data Strategy, AI & Knowledge Enablement, this role is an opportunity to contribute at the center of AbbVie’s R&D data transformation. The data foundations you build will help determine which analytics, knowledge graph, and AI use cases are possible across research - and how confidently the organization can use their output to support scientific decision-making.\nResponsibilities\nAI-Ready Data Product Engineering: Design, build, and operate curated, 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. \nTrusted Data Foundation Enablement: Establish reliable, 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. \nAI, RAG & Knowledge Graph Readiness: Prepare data and documents for AI and knowledge discovery use cases by cleaning, standardizing, enriching, labeling, organizing metadata, supporting chunking, and embedding workflows, and producing vector database-ready assets. Enable publication of curated data to the ARCH knowledge graph. \nData 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. \nTechnical 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. Provide technical guidance to contracted engineers, clarify work, review outputs, help remove barriers, and support delivery against agreed quality and acceptance standards. \nOperational Reliability & Continuous Improvement: Monitor pipeline performance, data freshness, cost, failures, and delivery issues; troubleshoot and resolve problems before they impact data consumers. Contribute to reusable engineering patterns, automation, process improvements, and consistent ways of working across data product workflows. \nCompliance & Standards: Follow applicable Corporate and Divisional policies, including GxP compliance, data security, software development lifecycle practices, data governance standards, and relevant regulatory or contractual requirements. \n Required:\nBachelor’s Degree with 5 years of experience; OR Master’s Degree with 4 years of experience in information technology, data engineering, data management, analytics, life sciences, or a related field.\nHands-on experience designing, developing, and operating production data pipelines and curated data products using SQL, Python, ETL/ELT patterns, and workflow orchestration tools such as Airflow. \nWorking knowledge of modern data platforms, data integration, data warehousing or lakehouse patterns, distributed SQL or big data environments, cloud infrastructure, and analytics enablement. \nExperience preparing data for downstream analytics, machine learning, knowledge graph, or retrieval use cases, including cleaning, standardization, enrichment, structuring, metadata organization, and support for embedding or vector-search workflows. \nExperience applying data quality, metadata management, governance, lineage, documentation, and data modeling practices to support trusted, reusable data products. \nExperience collaborating with cross-functional business, scientific, technical, platform, vendor, contractor, or managed-services teams to translate requirements and deliver fit-for-purpose data assets. \nAbility to operate with a high degree of autonomy, manage priorities across concurrent workstreams, modify approach when needed, escalate open issues, and keep stakeholders informed through clear written and verbal communication. \nDemonstrated ability to learn, understand, and apply new data engineering, platform, and AI-enablement technologies, and to serve as a technical resource for others. \nExperience providing technical input, clarifying requirements, and reviewing outputs from contracted, vendor, or managed-services engineers without direct reporting authority. \nStrong communication, planning, and organizational skills, with the ability to explain technical concepts and keep stakeholders informed. \nData product engineering mindset, with the ability to shape reusable, well-structured data assets that are practical, scalable, and fit for analytics and AI-enabled use. \nData curation and stewardship mindset, with attention to quality, metadata, lineage, governance, standards, documentation, and appropriate use. \nTechnical fluency across data platforms, pipelines, integration patterns, orchestration, cloud environments, and data delivery practices sufficient to work effectively with engineering and platform teams. \nOperational discipline across monitoring, troubleshooting, prioritization, issue resolution, automation, reusable patterns, and continuous improvement. \nTechnical coordination and influence, with the ability to clarify priorities, guide work, review outputs, resolve ambiguity, and coordinate across internal and external contributors. \nStakeholder communication, with the ability to frame tradeoffs, risks, dependencies, and progress in a clear and practical way for technical, scientific, and business audiences. \nPreferred:\nPharmaceutical or healthcare industry experience preferred. \nExperience supporting research, discovery, translational, clinical, scientific, or other life sciences data environments. \nFamiliarity with graph databases, knowledge graphs, ontology-based data structures, semantic data, metadata-driven data products, or linked-data concepts. \nExperience working with AWS-based, cloud-based, lakehouse, or modern data platform technologies such as Databricks, Spark, Snowflake, Neo4j, or similar tools. \nExperience working with regulated data environments, including data governance, documentation, security, privacy, license terms, or compliance expectations. \nExposure to analytics, machine learning, retrieval-augmented generation (RAG), embeddings, vector databases, AI-search patterns, or AI-ready data product delivery. \nFamiliarity with Agile practices or planning tools such as Jira, including backlog refinement, sprint planning, prioritization, acceptance criteria, and delivery tracking. \n Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:\nThe 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. \nWe offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.\nThis job is eligible to participate in our short-term incentive programs. \nNote: 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.\nAbbVie 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.\nUS & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html\nUS & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:\nhttps://www.abbvie.com/join-us/reasonable-accommodations.html","description_format":"text","description_chars":10568,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":["Vision insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Prescription Drugs","Oncology Therapeutics","Neurology & CNS Therapeutics","Immunology & Inflammation Therapeutics"],"lifecycle":[{"event":"open","at":"2026-09-16T12:41:11Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 236 · green card filings: 57","filings_12m":236,"filings_prev_12m":256,"green_card_filings_12m":57,"median_offered_wage_usd":150555,"route":null,"cap_exempt":false,"checked_at":"2026-10-29T16:27:21+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":75}],"liveness":{"score":12,"band":"cold","label":"Long shot","p_open":1,"p_active":0.426,"p_room":0.28,"age_days":44,"expected_fill_days":16,"reasons":["conf:1","stale_co","velocity","win:tail","crowd:brand"],"computed_at":"2026-10-30T05:48:23Z"},"pay":{"stated_usd_annual":162000,"is_top_pay":true},"html_url":"https://alion.io/job/abbvie-data-engineer-ai-enablement","json_url":"https://alion.io/job/abbvie-data-engineer-ai-enablement.json","meta":{"generated_at":"2026-10-31T06:02:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":8744,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3660},"rest":"https://alion.io/mcp/rest/get_company?id=3660"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fabbvie-data-engineer-ai-enablement"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fabbvie-data-engineer-ai-enablement"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fabbvie-data-engineer-ai-enablement"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/abbvie-data-engineer-ai-enablement\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fabbvie-data-engineer-ai-enablement"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":963828}},{"tool":"search_jobs","arguments":{"company":"abbvie.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":963828},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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