About the job
Bristol Myers Squibb (BMS) is hiring an Analytics Engineer I for its Commercial Data & AI team in Hyderabad. The role focuses on building reliable, analytics-ready datasets that support business dashboards, self-service reporting and advanced analytics.
You will work with SQL, Python and Databricks to transform structured and semi-structured data into reusable datasets and metrics. Working alongside senior engineers and a commercial business team, you will help develop data models, validate data quality, document data assets and follow governance practices for sensitive information.
This is an early-career opportunity for candidates with 1–3 years of experience in analytics engineering, data engineering, BI engineering or a related field.
What You’ll Do
- Build and maintain curated datasets, data products and reusable transformations for commercial reporting and analytics.
- Translate business requirements into data specifications, dimensional models, metric definitions and dataset readiness criteria.
- Develop SQL- and Python-based transformations for structured and semi-structured pharmaceutical datasets.
- Create fact tables, dimension tables, cross-domain joins and slowly changing dimensions to support reporting and analytics.
- Implement data quality checks, reconciliation routines, validation rules and anomaly detection controls.
- Improve reusable code patterns, templates and engineering practices to keep data products consistent and maintainable.
- Document data definitions, lineage, assumptions and known limitations.
- Collaborate with data engineers, analysts, BI developers and commercial stakeholders on dashboards and reporting requirements.
- Follow data governance, access control and secure handling practices for sensitive information, including personal and health-related data.
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 hands-on experience in analytics engineering, data engineering, BI engineering or a related role.
- Strong SQL skills for data transformation, modeling, validation and performance tuning.
- Working knowledge of Python for data preparation, validation and automation.
- Experience transforming large datasets with attention to data quality and performance.
- Understanding of dimensional modeling, including facts, dimensions, data grain, keys and slowly changing dimensions.
- Familiarity with ETL/ELT processes, lakehouse concepts and bronze, silver and gold data layers.
- Knowledge of data documentation, governance and secure data handling.
- Problem-solving, communication and collaboration skills.
Preferred Qualifications
- Hands-on familiarity with Databricks notebooks, jobs, workflows and Delta Lake.
- Experience with lakehouse architecture and medallion data architecture.
- Experience with pharmaceutical commercial datasets, such as claims, patient, sales, payer, HUB or specialty pharmacy data.
- Exposure to semantic layers, metric definitions, BI reporting and dashboard-ready data models.
- Familiarity with Tableau or Power BI.
- Experience with Git, code reviews, version control and basic CI/CD practices.
About the Team
The Commercial Data & AI team builds the analytics layer used by commercial business functions such as Sales, Marketing, Market Access and Medical Affairs. This role works alongside an assigned business domain to help ensure that datasets and metrics meet reporting and analytics needs.
Before You Apply
- Highlight your 1–3 years of experience building datasets, data pipelines or analytics assets.
- Include examples of SQL transformations, Python workflows, data validation and performance improvements.
- Describe any experience with dimensional modeling, fact and dimension tables, or slowly changing dimensions.
- If you have used Databricks, Delta Lake, Power BI, Tableau or Git, specify the tools and work you completed.
- Include relevant experience handling sensitive data, maintaining data quality or documenting data lineage.
Workplace and Application Information
The role is based in Hyderabad, Telangana. BMS uses several work models, including site-essential, site-by-design, field-based and remote-by-design. The specific work model for this position should be confirmed through the employer’s application page.
BMS encourages candidates to apply if the role interests them, even if their experience does not match every listed qualification. The company states that it does not request payments or financial information as part of its recruitment process.
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JobsInHyd does not guarantee hiring outcomes.About Bristol Myers Squibb
Bristol Myers Squibb is a biopharmaceutical company that develops medicines for serious diseases. Its work spans drug discovery, clinical development and commercial operations. This position sits within its Commercial Data & AI team.
Bristol Myers Squibb (BMS) is hiring an Analytics Engineer I for its Commercial Data & AI team in Hyderabad. The role focuses on building reliable, analytics-ready datasets that support business dashboards, self-service reporting and advanced analytics.
You will work with SQL, Python and Databricks to transform structured and semi-structured data into reusable datasets and metrics. Working alongside senior engineers and a commercial business team, you will help develop data models, validate data quality, document data assets and follow governance practices for sensitive information.
This is an early-career opportunity for candidates with 1–3 years of experience in analytics engineering, data engineering, BI engineering or a related field.
What You’ll Do
- Build and maintain curated datasets, data products and reusable transformations for commercial reporting and analytics.
- Translate business requirements into data specifications, dimensional models, metric definitions and dataset readiness criteria.
- Develop SQL- and Python-based transformations for structured and semi-structured pharmaceutical datasets.
- Create fact tables, dimension tables, cross-domain joins and slowly changing dimensions to support reporting and analytics.
- Implement data quality checks, reconciliation routines, validation rules and anomaly detection controls.
- Improve reusable code patterns, templates and engineering practices to keep data products consistent and maintainable.
- Document data definitions, lineage, assumptions and known limitations.
- Collaborate with data engineers, analysts, BI developers and commercial stakeholders on dashboards and reporting requirements.
- Follow data governance, access control and secure handling practices for sensitive information, including personal and health-related data.
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 hands-on experience in analytics engineering, data engineering, BI engineering or a related role.
- Strong SQL skills for data transformation, modeling, validation and performance tuning.
- Working knowledge of Python for data preparation, validation and automation.
- Experience transforming large datasets with attention to data quality and performance.
- Understanding of dimensional modeling, including facts, dimensions, data grain, keys and slowly changing dimensions.
- Familiarity with ETL/ELT processes, lakehouse concepts and bronze, silver and gold data layers.
- Knowledge of data documentation, governance and secure data handling.
- Problem-solving, communication and collaboration skills.
Preferred Qualifications
- Hands-on familiarity with Databricks notebooks, jobs, workflows and Delta Lake.
- Experience with lakehouse architecture and medallion data architecture.
- Experience with pharmaceutical commercial datasets, such as claims, patient, sales, payer, HUB or specialty pharmacy data.
- Exposure to semantic layers, metric definitions, BI reporting and dashboard-ready data models.
- Familiarity with Tableau or Power BI.
- Experience with Git, code reviews, version control and basic CI/CD practices.
About the Team
The Commercial Data & AI team builds the analytics layer used by commercial business functions such as Sales, Marketing, Market Access and Medical Affairs. This role works alongside an assigned business domain to help ensure that datasets and metrics meet reporting and analytics needs.
Before You Apply
- Highlight your 1–3 years of experience building datasets, data pipelines or analytics assets.
- Include examples of SQL transformations, Python workflows, data validation and performance improvements.
- Describe any experience with dimensional modeling, fact and dimension tables, or slowly changing dimensions.
- If you have used Databricks, Delta Lake, Power BI, Tableau or Git, specify the tools and work you completed.
- Include relevant experience handling sensitive data, maintaining data quality or documenting data lineage.
Workplace and Application Information
The role is based in Hyderabad, Telangana. BMS uses several work models, including site-essential, site-by-design, field-based and remote-by-design. The specific work model for this position should be confirmed through the employer’s application page.
BMS encourages candidates to apply if the role interests them, even if their experience does not match every listed qualification. The company states that it does not request payments or financial information as part of its recruitment process.