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Bristol Myers Squibb

Makes drugs for cancer, blood and immune diseases

Analytics Engineer 1 - Commercialization

Data EngineeringConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

  • Strong proficiency in SQL for analytics transformations, data modeling, validation, and performance tuning.
  • Working knowledge of Python for data preparation, validation, automation, and analytical workflows.
  • Experience developing analytics-ready datasets using dimensional modeling concepts such as facts, dimensions, grains, keys, and slowly changing dimensions.
  • Familiarity with ETL/ELT patterns, lakehouse concepts, and medallion architecture, including bronze, silver, and gold/refined layers.
  • Hands-on familiarity with Databricks notebooks, jobs/workflows, and Delta Lake concepts.
  • Understanding of semantic layer concepts, metric definitions, and how curated datasets support business intelligence, dashboards, and self-service analytics.
  • Experience with data quality practices including profiling, cleansing, standardization, reconciliation, and anomaly detection.
  • Working knowledge of governance and secure data handling practices, including documentation, lineage, and access controls.
  • Familiarity with business intelligence and visualization tools such as Tableau or Power BI.
  • Understanding of engineering practices such as Git/version control, code reviews, and basic CI/CD concepts.
  • Strong problem-solving and communication skills, with the ability to work effectively with both technical and business stakeholders.
  • Willingness to work as part of a deployed team embedded within a business domain, learning to adapt to domain-specific priorities.
  • A bachelor's or master's degree in Computer Science, Engineering, Information Systems, Statistics/Mathematics, Analytics, or a related field, or equivalent practical experience.
  • One to three years of hands-on experience in analytics engineering, data engineering, business intelligence engineering, or a related role building curated datasets and analytics-ready assets.
  • Experience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance.

Responsibilities

  • Design, 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.
  • Translate business and analytics requirements into clear data specifications, dimensional models, metrics definitions, and dataset readiness criteria aligned to internal modeling and delivery standards.
  • Develop and maintain scalable SQL- and Python-based transformation logic that integrates structured and semi-structured pharmaceutical datasets such as claims, patient, sales, payer, HUB, and specialty pharmacy data.
  • Apply internally developed accelerators, reusable code patterns, templates, and engineering guardrails to improve development speed, consistency, and maintainability across data products.
  • Create 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.
  • Implement standardized data quality checks, reconciliation logic, validation routines, and anomaly detection controls to ensure datasets are accurate, complete, and trusted by downstream users.
  • Document data products, metric definitions, lineage, assumptions, and known limitations in accordance with internal documentation and governance standards.
  • Work as part of a deployed engineering team embedded alongside an assigned Commercial business domain, partnering with data engineers, analysts, business intelligence developers, and business stakeholders to support dashboard and reporting use cases.
  • Apply data governance standards, access controls, and compliant handling practices for sensitive and regulated data, including personally identifiable information and protected health information awareness.

Desired Qualifications

  • Experience with Databricks, Delta Lake, or lakehouse architecture.
  • Experience working with commercial pharmaceutical datasets such as claims, sales, payer, patient, HUB, or specialty pharmacy data.
  • Exposure to business intelligence/reporting use cases, semantic layer design, or dashboard-ready data modeling.

About the Company

Bristol Myers Squibb

Makes drugs for cancer, blood and immune diseases

Bristol Myers Squibb discovers, develops and sells prescription medicines for serious illnesses, including cancer, blood disorders, immune diseases and heart disease, for patients treated by doctors and hospitals around the world. Its best-known drug is Opdivo, an immunotherapy that helps the body's own immune system find and attack many kinds of cancer. Researchers develop drug candidates in its labs or bring them in through acquisitions and partnerships, then test them in clinical trials to win regulatory approval. The company makes and markets the approved medicines and earns its revenue from sales of patent-protected drugs. Its roots go back to a business founded in 1887, and it is based in Lawrence Township, New Jersey.

Company size
10,001+
Company stage
IPO
Headquarters
Lawrence Township, NJ
Founded
1887

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