{"id":3390162,"url":"https://alion.io/job/bristol-myers-squibb-analytics-engineer-i-commercialization-3","title":"Analytics Engineer I , Commercialization","company":{"id":7994,"name":"Bristol Myers Squibb","domain":"bms.com","url":"https://alion.io/company/bms","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":90,"open_postings":42,"ghost_share":0.024,"stale_share":0.31,"repost_share":0.024,"time_to_fill_p50_days":23,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Analytics","role_family":"Analytics","seniority":"junior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":9000,"max_usd":20000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":13},"experience_years_min":1,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Tableau","optional":false}],"status":"live","first_seen_at":"2026-10-28T09:36:14Z","employer_posted_date":"2026-10-28","last_verified_at":"2026-11-02T12:07:44Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"At Bristol Myers Squibb, our employees often ask, “Who are you working for?”-a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.\nKey Responsibilities\nDesign, build, and support analytics-ready data products, curated datasets, and reusable transformation assets within a modern lakehouse environment to enable commercial reporting, self-service analytics, and business insights.\nTranslate business and analytics requirements into clear data specifications, dimensional models, metrics definitions, and dataset readiness criteria aligned to internal modeling and delivery standards.\nDevelop and maintain scalable SQL- and Python-based transformation logic that integrates structured and semi-structured pharma datasets such as claims, patient, sales, payer, HUB, and specialty pharmacy data.\nApply internally developed accelerators, reusable code patterns, templates, and engineering guardrails to improve development speed, consistency, and maintainability across data products.\nCreate analytics-friendly models, including fact and dimension tables, cross-domain joins, slowly changing dimensions, and business-rule-driven metrics that support dashboard, reporting, and advanced analytics consumption.\nImplement standardized data quality checks, reconciliation logic, validation routines, and anomaly detection controls to ensure datasets are accurate, complete, and trusted by downstream users.\nDocument data products, metric definitions, lineage, assumptions, and known limitations in accordance with internal documentation and governance standards.\nWork as part of a deployed engineering team embedded alongside an assigned Commercial business domain, partnering with data engineers, analysts, BI developers, and business stakeholders to support dashboard and reporting use cases.\nApply data governance standards, access controls, and compliant handling practices for sensitive and regulated data, including PII/PHI awareness.\nSkills & Competencies\nStrong proficiency in SQL for analytics transformations, data modeling, validation, and performance tuning.\nWorking knowledge of Python for data preparation, validation, automation, and analytical workflows.\nExperience developing analytics-ready datasets using dimensional modeling concepts such as facts, dimensions, grains, keys, and slowly changing dimensions.\nFamiliarity with ETL/ELT patterns, lakehouse concepts, and medallion architecture, including bronze, silver, and gold/refined layers.\nHands-on familiarity with Databricks notebooks, jobs/workflows, and Delta Lake concepts.\nUnderstanding of semantic layer concepts, metric definitions, and how curated datasets support BI, dashboards, and self-service analytics.\nExperience with data quality practices including profiling, cleansing, standardization, reconciliation, and anomaly detection.\nWorking knowledge of governance and secure data handling practices, including documentation, lineage, and access controls.\nFamiliarity with BI/visualization tools such as Tableau or Power BI.\nUnderstanding of engineering practices such as Git/version control, code reviews, and basic CI/CD concepts.\nStrong problem-solving and communication skills, with the ability to work effectively with both technical and business stakeholders.\nWillingness to work as part of a deployed team embedded within a business domain, learning to adapt to domain-specific priorities.\n Qualifications & Experience\nA bachelor's or master's degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, Analytics, or a related field (or equivalent practical experience).\n1-3 years of hands-on experience in analytics engineering, data engineering, business intelligence engineering, or a related role building curated datasets and analytics-ready assets.\nExperience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance.\nPreferred: experience with Databricks, Delta Lake, or lakehouse architecture.\nPreferred: experience working with commercial pharma datasets such as claims, sales, payer, patient, HUB, or specialty pharmacy data.\nPreferred: exposure to BI/reporting use cases, semantic layer design, or dashboard-ready data modeling.\nWe hire for skills and capabilities, not just credentials - if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.\nHow We Work\nWhere you work matters - because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.\nSupporting People with Disabilities\nBMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to . Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.\nCandidate Rights\nBMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.\nFor roles based in Los Angeles County only: If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/\nFor roles based in Washington State only: If you live in or expect to work from Washington State if hired for this position, please visit this page for important information about the Washington Fair Chance Act.\nData Protection\nWe will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection.\nAny data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.\nIf this posting is missing required information required by local law or incorrect, contact BMS at  with the Job Title and Requisition number. Do not send application-related inquiries to this email. 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