{"id":180626,"url":"https://alion.io/job/vizient-senior-artificial-intelligence-data-engineer","title":"Senior Artificial Intelligence Data Engineer","company":{"id":15164,"name":"Vizient","domain":"vizient.com","url":"https://alion.io/company/vizient","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":8,"ghost_share":0,"stale_share":0.625,"repost_share":0,"time_to_fill_p50_days":43,"computed_at":"2026-10-01T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Irving, United States","Chicago, United States","United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":102400,"max":179000,"currency":"USD","period":"year","gross":null,"usd_annual":179000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentic Workflows","optional":false},{"name":"AI Agents","optional":false},{"name":"Apache Iceberg","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"Git","optional":false},{"name":"Kubernetes","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Pulumi","optional":false},{"name":"pySpark","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Trino","optional":false},{"name":"Python","optional":true}],"status":"live","first_seen_at":"2026-08-20T00:00:00Z","employer_posted_date":"2026-08-20","last_verified_at":"2026-10-01T06:44:00Z","board_verified":true,"closed_at":null,"days_open":42,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":42},"description":"When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.\nSummary\nIn this role, you will help build and enhance a modern, AI-ready data enablement platform that supports cross-domain analytics, governed data products, and reusable engineering patterns across the enterprise. You will enable data producers and analytics teams through guided pathways, reusable accelerators, metadata-driven frameworks, CI/CD patterns, Databricks Asset Bundles, dbt transformation standards, Unity Catalog governance, and Starburst/Trino analytical access. You will focus on helping teams create trusted, governed, reusable, and AI-ready derivative data products that support analytics, reporting, GenAI, semantic search, and emerging agentic platform use cases. As a hands-on senior individual contributor, you will combine platform engineering, data transformation, governance, and enablement to drive scalable and repeatable data product delivery across the organization.\nResponsibilities\nBuild and support scalable data engineering solutions using Azure Databricks, PySpark, SQL, Delta Lake, Azure Data Factory, dbt, and Unity Catalog.\nImprove metadata-driven Azure Data Factory and Databricks patterns for orchestration, configuration, monitoring, restartability, and operational support.\nDevelop reusable accelerators including CI/CD templates, Databricks Asset Bundle patterns, deployment automation, environment configuration, and data product onboarding templates.\nDesign, develop, and support dbt models, macros, tests, documentation, and transformation standards for governed analytical data products.\nProvide guidance on appropriate technology selection and implementation patterns across dbt, Databricks notebooks and workflows, Delta Live Tables, Spark, and Starburst/Trino.\nSupport cross-domain analytics initiatives by transforming source-refined data into trusted, reusable, business-aligned derivative data products.\nLeverage Unity Catalog to establish and support governed catalogs, schemas, tables, lineage, access controls, naming standards, and certification practices.\nSupport Starburst/Trino as an analytical and federated query layer for governed enterprise data consumption.\nApply Azure DevOps, Git, CI/CD, and Infrastructure as Code (IaC) practices to create repeatable, testable, and environment-aware platform delivery processes.\nTroubleshoot and resolve production issues related to orchestration, transformations, data quality, access management, query performance, deployments, and operational workflows.\nCollaborate with data engineering, analytics, platform, governance, and business teams to establish reusable, scalable, and supportable data engineering patterns.\nContribute to the evolution of enterprise data engineering standards, governance practices, observability capabilities, and AI-ready data product frameworks.\nQualifications\nRelevant degree preferred.\n5 or more years of hands-on data engineering experience building production-grade data platforms, pipelines, or analytical data products required.\nStrong experience with Azure Databricks, PySpark, Spark SQL, Delta Lake, Azure Data Factory, SQL, and dbt required.\nExperience with Azure DevOps, Git, pull request workflows, CI/CD pipelines, and release management practices required.\nWorking knowledge of lakehouse architecture, metadata management, data governance, lineage, access control, and operational support required.\nDemonstrated ability to function as a senior individual contributor with strong ownership, technical judgment, and cross-functional collaboration skills required.\nExperience supporting enterprise-scale analytical platforms and governed data product delivery preferred.\nExperience with Unity Catalog, Starburst/Trino, Pulumi or other Infrastructure as Code tools, Databricks Asset Bundles, Apache Iceberg concepts, and AKS/Kubernetes-based platform operations preferred.\nExperience building reusable frameworks, accelerators, templates, or platform capabilities for engineering teams preferred.\nExperience preparing governed structured data for AI/ML, GenAI, Retrieval-Augmented Generation (RAG), semantic search, copilots, or agentic workflows preferred.\nExperience within healthcare, analytics, supply chain, finance, or other regulated enterprise environments preferred.\nStrong problem-solving, communication, and collaboration skills with the ability to influence technical direction and establish best practices preferred.\nYou must be authorized to work in the United States without sponsorship.\nEstimated Hiring Range:\nAt Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $102,400.00 to $179,000.00.This position is also incentive eligible.\nVizient has a comprehensive benefits plan! Please view our benefits here:\nhttp://www.vizientinc.com/about-us/careers\nEqual Opportunity Employer: Females/Minorities/Veterans/Individualswith Disabilities\nThe Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.","description_format":"text","description_chars":5774,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Professional development"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Medical Equipment Distribution","Health Data & Interoperability","Healthcare & Life Sciences Consulting"],"lifecycle":[{"event":"open","at":"2026-08-31T16:39:37Z"}],"liveness":{"score":45,"band":"ok","label":"Likely open","p_open":1,"p_active":0.755,"p_room":0.6,"age_days":42,"expected_fill_days":43,"reasons":["conf:19","velocity","win:late","crowd:brand"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":179000,"is_top_pay":true},"html_url":"https://alion.io/job/vizient-senior-artificial-intelligence-data-engineer","json_url":"https://alion.io/job/vizient-senior-artificial-intelligence-data-engineer.json","meta":{"generated_at":"2026-10-01T09:59:14Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":942,"day_limit":5000,"remaining_today":4058,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}