{"id":3653386,"url":"https://alion.io/job/merck-co-specialist-semantic-data-engineer","title":"Specialist, Semantic Data Engineer","company":{"id":3768,"name":"Merck & Co.","domain":"msd.com","url":"https://alion.io/company/msd","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":98,"open_postings":191,"ghost_share":0.026,"stale_share":0.105,"repost_share":0.173,"time_to_fill_p50_days":16,"computed_at":"2026-11-06T05:58:05Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Prague, Czech Republic","Hyderabad, India"],"countries":["CZ","IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Neptune","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Confluence","optional":false},{"name":"Docker","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Jira","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Terraform","optional":false},{"name":"AWS Lambda","optional":true},{"name":"AWS Step Functions","optional":true},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-11-02T00:00:00Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-06T05:00:30Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"Job Description\nOur company is seeking a semantic data engineer to build, and scale enterprise-grade knowledge graph solutions that power advanced analytics and decision-making in pharmaceutical research. This role will implement the design of semantic data layers that integrate heterogeneous scientific datasets, enabling end-to-end traceability, cross-domain insights, and AI/ML-driven discovery. The ideal candidate will combine deep expertise in knowledge graphs, ontology engineering, and data engineering, with strong domain awareness in pharmaceutical R&D.\nKey responsibilities\nDesign and implement scalable knowledge graph architectures to integrate multi-modal data (e.g., omics, process, analytical, lineage)\nBuild and manage graph data models representing entities such as samples, processes, assays, targets, and biological relationships\nDrive adoption of graph technologies (e.g., RDF, property graphs, SPARQL/Cypher)\nPartner with platform teams to implement scalable infrastructure (e.g., Amazon Neptune, serverless pipelines)\nEnsure performance, scalability, and governance of knowledge graph platforms\nCollaborate with product managers, scientists, data engineers, and AI/ML teams to translate business needs into semantic models\nRequired experience and skills\nSemantic web technology stack (e.g., RDF data format, SPARQL query language)\nAmazon Web Services (AWS), particularly the serverless services (e.g., Lambda, Step Functions)\nData engineering (e.g., SQL queries, ETL jobs)\nProgramming in Python\nExperience with DevSecOps practices like continuous integration (CI) and continuous delivery (CD), source code version control (e.g., Git), infrastructure-as-code (e.g., CloudFormation, Terraform), and containers (e.g., Docker)\nDesired experience and skills\nCheminformatics and familiarity with the pharmaceutical research\nExposure to AI/ML applications leveraging graph data\nGood communication and collaboration skills, and ability to collaborate with other teams to develop solutions\nExperience with Atlassian stack of tools for agile software development (e.g., Jira, Confluence)\nDemonstrate growth mindset and ability to work with enterprise teams\nAdditional location(s) Compensation Information:\nRequired Skills:\nAmazon Web Services (AWS), CI/CD, Collaboration, Communication, DevSecOps, Extract Transform Load (ETL), Graph Databases, Infrastructure As Code (IaC), Python (Programming Language), Resource Description Framework (RDF), SPARQL, Structured Query Language (SQL), Version ControlPreferred Skills:\nArtificial Intelligence (AI), Atlassian Confluence, Atlassian JIRA, AWS CloudFormation, Cheminformatics, Docker (Software), Git, Machine Learning (ML), Pharmaceutical Research, Terraform (Software)Current Employees apply HERE\nCurrent Contingent Workers apply HERE\nSearch Firm Representatives Please Read Carefully\nMerck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.\nEmployee Status:\nRegularRelocation:\nNo relocationVISA Sponsorship:\nYesTravel Requirements:\n10%Flexible Work Arrangements:\nHybridShift:\nNot IndicatedValid Driving License:\nNoHazardous Material(s):\nN/AJob Posting End Date:\n11/6/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. 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