{"id":3423361,"url":"https://alion.io/job/eli-lilly-and-company-data-engineer","title":"Data Engineer","company":{"id":1753780,"name":"Eli Lilly and Company","domain":"lilly.com","url":"https://alion.io/company/lilly-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":83,"open_postings":68,"ghost_share":0,"stale_share":0.897,"repost_share":0,"time_to_fill_p50_days":21,"computed_at":"2026-11-01T06:10:25Z"}},"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":["South San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":157500,"max":231000,"currency":"USD","period":"year","gross":null,"usd_annual":231000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Dagster","optional":false},{"name":"Dask","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Machine Learning","optional":false},{"name":"MQTT","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-28T21:35:50Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-01T21:29:03Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work-but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.\nWhere AI Meets Medicine: Build the Future of Drug Discovery in the Heart of Silicon Valley!\nMaking medicine that’s never been made means doing what’s never been done. If you’re an engineer, scientist, or builder who thrives on problems no one has solved before, this is your invitation; we want you on the team. We are ready to challenge the status quo and push medicine forward, all in the name of health. Are you up for the challenge? If so, join us!\nAbout the Lilly and NVIDIA Partnership\nLilly and NVIDIA are launching a new AI co-innovation lab in the heart of Silicon Valley - an up-to-$1 billion, multi-year commitment to solve drug discovery’s toughest challenges. The lab brings Lilly scientists, technologists, chemists and biologists together with NVIDIA engineers under one roof. Together, we are building purpose-built foundation and frontier AI models trained on Lilly data at scale, tightening the feedback loop between automated wet labs and computational dry labs, designing the next generation of medicines for millions of patients across the globe.\nWhat You’ll Be Doing\nAs a Data Engineer, you will build and maintain the data platforms that power AI-driven research and discovery. You will develop scalable pipelines that ingest, transform, and deliver chemical, biological, and experimental data for machine learning and scientific workflows. Partnering with AI Scientists, AI Engineers, and laboratory researchers, you will ensure that data is accurate, traceable, and accessible at scale. Your work will provide the trusted data foundation behind next-generation AI models and experiments.\nHow You’ll Succeed\nEngineer datasets in large language environment for model training specifically efficient formats and storage layout (Parquet, Zarr, Arrow)and delivery fast enough that GPU clusters are never left waiting on data.\n\nDesign, develop, and maintain scalable and efficient data pipelines to support data analytics, reporting, and machine learning initiatives.\n\nEnsure seamless data flow between systems and applications, optimizing data transfer and transformation processes for performance and scalability.\n\nBuild the ingestion path from the automated lab, so experimental results reach the models in hours rather than weeks, closing the loop between what a model proposes and what the next model learns from.\n\nOwn the correctness of what models train on completeness, sound joins across experimental sources, and validation that catches a bad dataset before it reaches a training run rather than after.\n\nBuild dataset versioning, lineage, and reproducibility into the platform, so any model can be traced to the exact data it was trained on months or years later.\n\nWork with the laboratory, instrument, and external teams producing the data so that a change upstream does not quietly corrupt a training run downstream.\n\nWhat You Should Bring\nStrong Python, or equivalent experience building data-intensive software systems.\n\nStrong SQL and data modeling experience including designing schemas that hold up as scientific data grows and diversifies, with expert knowledge of Postgres or a comparable enterprise database.\n\nDistributed data processing (Spark, Ray, or Dask) and pipeline orchestration (Airflow or Dagster) at scale.\n\nExperience with cloud platforms - AWS and Azure preferred - and with high-performance and object storage feeding large-scale compute environments.\n\nA track record of building data systems that other people depend on, and of taking responsibility for them when they broke.\n\nStrong testing practices and test automation, with solid CI/CD and Git fundamentals.\n\nAdaptability and a collaborative mindset, with the ability to translate complex scientific questions into data solutions that accelerate experimentation and decision-making.\n\nExperience streaming and event-driven integration (Kafka, MQTT, or AMQP), including instrument and laboratory data capture.\n\nCheminformatics or scientific data experience - compound registration, structure notation (SMILES, InChI, HELM), RDKit, multi-omics, assay, or sequencing data - is a strong plus.\n\nPrior experience across the following: data modeling, ETL/ELT at scale, ontology development, semantic graph construction and linked data, or relational schema design.\n\nExperience standing up, migrating, or consolidating databases and data platforms, including production cutover of systems in active use.\n\nYour Basic Qualifications\nBachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field.\n\n5+ years of data engineering experience building and operating production data systems.\n\nLocation & Work Flexibility\nThis role is based at our Silicon Valley Hub. We offer a flexible hybrid work model, with three days onsite and two days working remotely each week, supporting both collaboration and work-life balance.\nLilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.\nLilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.\nOur employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).\nActual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is\n$157,500 - $231,000Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.","description_format":"text","description_chars":7839,"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":[]},"benefits":["Hybrid work","Life insurance"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Prescription Drugs","Oncology Therapeutics","Cardiometabolic Therapeutics"],"lifecycle":[{"event":"open","at":"2026-10-28T21:35:50Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 420 · green card filings: 30","filings_12m":420,"filings_prev_12m":452,"green_card_filings_12m":30,"median_offered_wage_usd":141567,"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":85}],"liveness":{"score":63,"band":"ok","label":"Likely open","p_open":1,"p_active":0.632,"p_room":1,"age_days":3,"expected_fill_days":21,"reasons":["conf:6","stale_co","velocity","win:early","comp:brand"],"computed_at":"2026-11-01T06:10:25Z"},"pay":{"stated_usd_annual":231000,"is_top_pay":true},"html_url":"https://alion.io/job/eli-lilly-and-company-data-engineer","json_url":"https://alion.io/job/eli-lilly-and-company-data-engineer.json","meta":{"generated_at":"2026-11-02T03:48:31Z","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":5584,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-03T00:00:00Z"}},"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":1753780},"rest":"https://alion.io/mcp/rest/get_company?id=1753780"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Feli-lilly-and-company-data-engineer"},{"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%2Feli-lilly-and-company-data-engineer"},{"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%2Feli-lilly-and-company-data-engineer"},{"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/eli-lilly-and-company-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Feli-lilly-and-company-data-engineer"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3423361}},{"tool":"search_jobs","arguments":{"company":"lilly.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3423361},"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); 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