About the job
Bristol Myers Squibb (BMS) is hiring an Analytics Engineer I for its Commercial Data & AI team in Hyderabad, Telangana. The role focuses on building and maintaining analytics-ready datasets that support business dashboards, self-service reporting and advanced analytics.
You will work with senior engineers, data engineers, analysts, BI developers and business stakeholders to turn business requirements into reliable data models and reusable SQL- and Python-based transformations. The work includes data quality checks, reporting metrics, documentation and governance within a Databricks-based lakehouse environment.
This is an early-career opportunity for candidates with 1–3 years of relevant experience in analytics engineering, data engineering, business intelligence engineering or a related field. Experience with Databricks, Delta Lake and pharmaceutical commercial datasets is preferred.
Job Details
- Company: Bristol Myers Squibb (BMS)
- Job Title: Analytics Engineer I, Commercialization
- Job Requisition ID: R1607232
- Location: Hyderabad, Telangana, India
- Experience: 1–3 years
- Salary: Not specified
- Employment Type: Full-time
- Work Model: Not specified in the supplied posting
- Team: Commercial Data & AI
- Job Level: Analytics Engineer I
What You’ll Do
- Build and maintain curated datasets and reusable data transformations for commercial reporting, dashboards and advanced analytics.
- Convert business requirements into data specifications, dimensional models, metric definitions and dataset readiness criteria.
- Develop and maintain SQL- and Python-based transformations for structured and semi-structured datasets.
- Create fact tables, dimension tables, cross-domain joins and business-rule-based metrics for reporting and analysis.
- Implement data quality checks, reconciliation logic, validation routines and anomaly detection controls.
- Document data products, metric definitions, data lineage, assumptions and known limitations.
- Work with data engineers, analysts, BI developers and business stakeholders to support reporting requirements.
- Apply data governance standards, access controls and appropriate handling practices for sensitive information.
- Use reusable code patterns, templates and engineering standards to improve consistency and maintainability.
What You Need
- A bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, Statistics, Mathematics, Analytics or a related field, or equivalent practical experience.
- 1–3 years of experience in analytics engineering, data engineering, BI engineering or a related role involving curated datasets and analytics-ready data assets.
- Strong SQL skills for data transformations, modeling, validation and performance tuning.
- Working knowledge of Python for data preparation, validation, automation and analytical workflows.
- Understanding of dimensional data modeling, including facts, dimensions, data grain, keys and slowly changing dimensions.
- Familiarity with ETL/ELT workflows, lakehouse concepts and medallion architecture.
- Understanding of data quality, profiling, cleansing, standardization and reconciliation.
- Knowledge of data documentation, lineage, governance and secure data handling.
- Good problem-solving and communication skills, with the ability to work with technical and business teams.
Preferred Qualifications
- Experience with Databricks, Delta Lake or lakehouse architecture.
- Familiarity with Databricks notebooks, jobs, workflows and related development tools.
- Experience working with pharmaceutical commercial datasets, such as claims, patient, sales, payer, HUB or specialty pharmacy data.
- Exposure to BI reporting, semantic layers, metric definitions or dashboard-ready data modeling.
- Familiarity with Tableau or Power BI.
- Knowledge of Git, version control, code reviews and basic CI/CD practices.
- Awareness of personally identifiable information (PII), protected health information (PHI) and relevant data protection practices.
Technical Skills
- Querying and transformation: SQL, Python
- Data platform: Databricks, Delta Lake
- Data engineering: ETL/ELT, lakehouse architecture, medallion architecture
- Data modeling: Dimensional modeling, fact tables, dimension tables, slowly changing dimensions
- Data quality: Data validation, profiling, reconciliation, cleansing and anomaly detection
- Business intelligence: Tableau, Power BI and semantic layer concepts
- Engineering practices: Git, version control, code reviews and basic CI/CD
- Governance: Data lineage, documentation, access controls and secure data handling
What You’ll Work With
The role supports commercial business functions such as Sales, Marketing, Market Access and Medical Affairs. Depending on the assigned business domain, the datasets may include claims, patient, sales, payer, HUB and specialty pharmacy information.
You will help prepare data for downstream dashboards, reporting and advanced analytics. The position also involves maintaining clear definitions, validation rules and documentation so that analysts and business users can work with consistent data.
About the Work Environment
- Work as part of an engineering team aligned with a commercial business domain.
- Collaborate with senior engineers and cross-functional stakeholders.
- Follow established engineering, documentation and data governance practices.
- Handle sensitive or regulated data in accordance with applicable internal controls.
How to Apply
- Review the required qualifications and technical skills listed above.
- Update your resume to highlight relevant SQL, Python, data modeling and data transformation experience.
- Include practical projects involving analytics-ready datasets, data quality checks, ETL/ELT pipelines or BI reporting where applicable.
- Use the Apply on Original Source ↗ button in the job page’s top section to open the original Bristol Myers Squibb application page.
- Review the application form and submit your details through the employer’s website.
Before You Apply
- Prepare examples of SQL queries used for joins, aggregations, transformations and data validation.
- Be ready to explain dimensional modeling, including fact tables, dimension tables, data grain, keys and slowly changing dimensions.
- Review Python techniques for data preparation, validation and automation.
- If you have used Databricks or Delta Lake, prepare to discuss your work with notebooks, workflows, data transformations or lakehouse architecture.
- Prepare an example of how you identified a data quality issue and validated or corrected the underlying data.
- Review data governance, lineage and the handling of sensitive information, including PII and PHI.
Important Information
The advertised experience requirement is 1–3 years. The employer does not specify a salary in the supplied posting. Databricks, Delta Lake, pharmaceutical commercial datasets and BI tools are listed as preferred experience areas, not universal mandatory requirements.
Bristol Myers Squibb states that it considers skills and capabilities alongside credentials and encourages interested candidates to apply even if their experience does not match every qualification.
Job Details
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JobsInHyd does not guarantee hiring outcomes.About Bristol Myers Squibb
Bristol Myers Squibb is a biopharmaceutical company focused on discovering, developing and delivering medicines for serious diseases. The company works across drug research, development and commercialization.
Bristol Myers Squibb (BMS) is hiring an Analytics Engineer I for its Commercial Data & AI team in Hyderabad, Telangana. The role focuses on building and maintaining analytics-ready datasets that support business dashboards, self-service reporting and advanced analytics.
You will work with senior engineers, data engineers, analysts, BI developers and business stakeholders to turn business requirements into reliable data models and reusable SQL- and Python-based transformations. The work includes data quality checks, reporting metrics, documentation and governance within a Databricks-based lakehouse environment.
This is an early-career opportunity for candidates with 1–3 years of relevant experience in analytics engineering, data engineering, business intelligence engineering or a related field. Experience with Databricks, Delta Lake and pharmaceutical commercial datasets is preferred.
Job Details
- Company: Bristol Myers Squibb (BMS)
- Job Title: Analytics Engineer I, Commercialization
- Job Requisition ID: R1607232
- Location: Hyderabad, Telangana, India
- Experience: 1–3 years
- Salary: Not specified
- Employment Type: Full-time
- Work Model: Not specified in the supplied posting
- Team: Commercial Data & AI
- Job Level: Analytics Engineer I
What You’ll Do
- Build and maintain curated datasets and reusable data transformations for commercial reporting, dashboards and advanced analytics.
- Convert business requirements into data specifications, dimensional models, metric definitions and dataset readiness criteria.
- Develop and maintain SQL- and Python-based transformations for structured and semi-structured datasets.
- Create fact tables, dimension tables, cross-domain joins and business-rule-based metrics for reporting and analysis.
- Implement data quality checks, reconciliation logic, validation routines and anomaly detection controls.
- Document data products, metric definitions, data lineage, assumptions and known limitations.
- Work with data engineers, analysts, BI developers and business stakeholders to support reporting requirements.
- Apply data governance standards, access controls and appropriate handling practices for sensitive information.
- Use reusable code patterns, templates and engineering standards to improve consistency and maintainability.
What You Need
- A bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, Statistics, Mathematics, Analytics or a related field, or equivalent practical experience.
- 1–3 years of experience in analytics engineering, data engineering, BI engineering or a related role involving curated datasets and analytics-ready data assets.
- Strong SQL skills for data transformations, modeling, validation and performance tuning.
- Working knowledge of Python for data preparation, validation, automation and analytical workflows.
- Understanding of dimensional data modeling, including facts, dimensions, data grain, keys and slowly changing dimensions.
- Familiarity with ETL/ELT workflows, lakehouse concepts and medallion architecture.
- Understanding of data quality, profiling, cleansing, standardization and reconciliation.
- Knowledge of data documentation, lineage, governance and secure data handling.
- Good problem-solving and communication skills, with the ability to work with technical and business teams.
Preferred Qualifications
- Experience with Databricks, Delta Lake or lakehouse architecture.
- Familiarity with Databricks notebooks, jobs, workflows and related development tools.
- Experience working with pharmaceutical commercial datasets, such as claims, patient, sales, payer, HUB or specialty pharmacy data.
- Exposure to BI reporting, semantic layers, metric definitions or dashboard-ready data modeling.
- Familiarity with Tableau or Power BI.
- Knowledge of Git, version control, code reviews and basic CI/CD practices.
- Awareness of personally identifiable information (PII), protected health information (PHI) and relevant data protection practices.
Technical Skills
- Querying and transformation: SQL, Python
- Data platform: Databricks, Delta Lake
- Data engineering: ETL/ELT, lakehouse architecture, medallion architecture
- Data modeling: Dimensional modeling, fact tables, dimension tables, slowly changing dimensions
- Data quality: Data validation, profiling, reconciliation, cleansing and anomaly detection
- Business intelligence: Tableau, Power BI and semantic layer concepts
- Engineering practices: Git, version control, code reviews and basic CI/CD
- Governance: Data lineage, documentation, access controls and secure data handling
What You’ll Work With
The role supports commercial business functions such as Sales, Marketing, Market Access and Medical Affairs. Depending on the assigned business domain, the datasets may include claims, patient, sales, payer, HUB and specialty pharmacy information.
You will help prepare data for downstream dashboards, reporting and advanced analytics. The position also involves maintaining clear definitions, validation rules and documentation so that analysts and business users can work with consistent data.
About the Work Environment
- Work as part of an engineering team aligned with a commercial business domain.
- Collaborate with senior engineers and cross-functional stakeholders.
- Follow established engineering, documentation and data governance practices.
- Handle sensitive or regulated data in accordance with applicable internal controls.
How to Apply
- Review the required qualifications and technical skills listed above.
- Update your resume to highlight relevant SQL, Python, data modeling and data transformation experience.
- Include practical projects involving analytics-ready datasets, data quality checks, ETL/ELT pipelines or BI reporting where applicable.
- Use the Apply on Original Source ↗ button in the job page’s top section to open the original Bristol Myers Squibb application page.
- Review the application form and submit your details through the employer’s website.
Before You Apply
- Prepare examples of SQL queries used for joins, aggregations, transformations and data validation.
- Be ready to explain dimensional modeling, including fact tables, dimension tables, data grain, keys and slowly changing dimensions.
- Review Python techniques for data preparation, validation and automation.
- If you have used Databricks or Delta Lake, prepare to discuss your work with notebooks, workflows, data transformations or lakehouse architecture.
- Prepare an example of how you identified a data quality issue and validated or corrected the underlying data.
- Review data governance, lineage and the handling of sensitive information, including PII and PHI.
Important Information
The advertised experience requirement is 1–3 years. The employer does not specify a salary in the supplied posting. Databricks, Delta Lake, pharmaceutical commercial datasets and BI tools are listed as preferred experience areas, not universal mandatory requirements.
Bristol Myers Squibb states that it considers skills and capabilities alongside credentials and encourages interested candidates to apply even if their experience does not match every qualification.