{"id":4301309,"url":"https://alion.io/job/md-anderson-cancer-center-remote-data-engineer-data-al-solution","title":"[Remote] Data Engineer - Data & AL Solution","company":{"id":1757439,"name":"MD Anderson Cancer Center","domain":"mdanderson.org","url":"https://alion.io/company/mdanderson","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"junior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":106000,"max":160000,"currency":"USD","period":"year","gross":null,"usd_annual":160000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":true,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"Power BI","optional":false}],"status":"live","first_seen_at":"2026-11-14T02:16:41Z","employer_posted_date":null,"last_verified_at":"2026-11-14T02:16:41Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Note: The job is a remote job and is open to candidates in USA. UT MD Anderson Cancer Center is hiring a Data Engineer to advance enterprise data engineering and analytics initiatives supporting institutional priorities. The role develops and supports scalable data pipelines, trusted data access, governance practices, analytics solutions, and the Context Engine framework, while collaborating with technical and business stakeholders.\n\nResponsibilities\nParticipate in end-to-end solution delivery that increases information capabilities and realizes data value across the institution\nBuild and support data sources and tools across the Context Engine framework through ingestion, ingress, egress, curation, transformation, modeling, and integration activities\nSupport existing end-to-end data pipelines from acquisition and integration through analytics consumption\nParticipate in planning, architecture, analysis, design, and implementation of enterprise data pipelines and solutions\nIncorporate repeatable solution designs and data models into enterprise data solutions\nExplore and promote modern tools, technologies, and architectures that automate repeatable data preparation and integration activities\nSupport data governance processes that track data provenance, security, data quality, and ontology throughout the data lifecycle\nIntegrate metadata management and governance processes into ingestion, curation, and pipeline development activities\nBuild data curation pipelines that include profiling, specification creation, cleansing, transformation, standardization, mastering, harmonization, validation, aggregation, and monitoring\nCreate, improve, and operationalize integrated and reusable data pipelines\nEnable faster access to trusted data and maximize data reuse across the enterprise\nAdhere to effective data management practices and promote understanding of data and analytics\nPartner with Information Systems, Data Offices, Data Governance teams, and other stakeholders to manage institutional data efficiently\nPartner with Enterprise Development & Integration and Enterprise Data Science teams to deliver analytics solutions\nCollaborate creatively with Principal and Senior Data Engineers and enterprise technology teams on solution delivery initiatives\nSupport institutional data strategy initiatives, including Context Engine objectives\nSupport customer relationships and collaborate with OneIS to deliver effective technical solutions and service\nAdhere to Information Systems standard operating procedures, institutional policies, and data stewardship requirements\nParticipate in development and maintenance of technical documentation for enhancements and new technologies\nFollow documented change control procedures and participate in change control audits when required\nPerform quality control testing and review solutions to ensure technical soundness\nAssist with analytics platform updates and new-release implementation activities\nAdhere to regulatory requirements, quality standards, and industry best practices\nCollaborate with internal and external stakeholders to maintain effective processes and systems\nParticipate in after-hours application support and downtime procedures\nTrain data scientists, data analysts, end users, and other data consumers on data pipelining and preparation techniques\nAssist with development of training plans for Context Engine tools and related systems\nPartner with training teams and subject matter experts to develop educational curricula\nProvide institutional, departmental, and individual training on Enterprise Data Engineering & Analytics deliverables\nSupport OneIS commitments by delivering innovative, high-quality, and sustainable information technology solutions and services\nPromote integrity, trust, respect, support, and honesty with customers and colleagues\nBuild productive, collaborative, and trusted partnerships across the organization\nDemonstrate continuous improvement and commitment to delivering outcomes that exceed expectations\nPerform other duties as assigned\n\nSkills\nBachelor's Degree\n2 years Clinical, relevant healthcare information technology, or relevant business experience\nWith preferred degree, no experience required\nMay substitute required education with years of related experience on a one to one basis\nOne Epic Data Model certification must be maintained\nEPIC - EPIC Certification Must obtain at least one Epic Data Model certification (Clinical, Access, or Revenue) issued by Epic. within 180 Days\nEPIC - Epic Accredited Must obtain at least one Epic Data Model accreditation (Clinical, Access, or Revenue) issued by Epic. within 180 Days\nMaster's Degree Business Analytics, Computer Science, Information Technology, Data Science, or related\nExperience with a modern data and analytics platform (Microsoft Fabric, Azure, Power BI, Palantir Foundry)\nAt least 2 years of hands-on work experience with AI/ML model and feature engineering processes\nProficiency in SQL\nMust understand how ontologies are structured and implementing semantic layers\n\nBenefits\nEmployer-paid medical coverage starting day one for employees working 30+ hours/week\nOptional group dental, vision, life, AD&D, and disability insurance\nAccruals for PTO and Extended Illness Bank\nPaid holidays, wellness, childcare, and other leave options\nTuition Assistance Program after six months of service\nAccess to extensive wellness, fitness, and employee resource groups\nDefined-benefit pension through the Teachers Retirement System\nVoluntary retirement plans\nEmployer-paid life and reduced salary protection programs\nRemote work within Texas only, with onsite presence a few times a year for key organizational/department meetings or key project/internal customer meetings; other onsite opportunities may be optional\nReferral bonus\nRelocation assistance\nEducational opportunities\nIndividual and team recognition\n\nCompany Overview\nThe University of Texas MD Anderson Cancer Center is one of the world’s most respected centers devoted exclusively to cancer patient care, research, education and prevention. It was founded in 1994, and is headquartered in Houston, Texas, USA, with a workforce of 10001+ employees. Its website is https://www.mdanderson.org/.\n\nCompany H1B Sponsorship\nUT MD Anderson has a track record of offering H1B sponsorships, with 190 in 2026, 265 in 2025, 191 in 2024, 174 in 2023, 168 in 2022, 124 in 2021, 73 in 2020. 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