Analytics Engineer I , Commercialization
Hyderabad - TS - IN
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingDocument data products, metric definitions, lineage, assumptions, and known limitations in accordance with internal documentation and governance standards.
From the employer’s posting
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, BI developers, and business stakeholders to support dashboard and reporting use cases.
What you’ll bring
All qualificationsCore experience
- 1–3 years of hands-on experience in analytics engineering, data engineering, business intelligence engineering, or a related role building curated datasets and analytics-ready assets.
- Experience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance.
Qualification wording
1–3 years of hands-on experience in analytics engineering, data engineering, business intelligence engineering, or a related role building curated datasets and analytics-ready assets.
Experience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance.
Education & alternatives
Qualifications & Experience - 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, business intelligence engineering, or a related role building curated datasets and analytics-ready assets.
Tools in this posting
- Python
- SQL
- Databricks
- Delta Lake
- Power BI
- Tableau
Source — Tool mentions in context
- 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 pharma 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.
- 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.
- 1–3 years of hands-on experience in analytics engineering, data engineering, business intelligence engineering, or a related role building curated datasets and analytics-ready assets. - Experience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance. - Preferred: experience with Databricks, Delta Lake, or lakehouse architecture.
Skills & Competencies - 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.
- 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 BI, dashboards, and self-service analytics.
- Experience transforming large-scale structured and semi-structured datasets using SQL and Python, with attention to data quality and performance. - Preferred: experience with Databricks, Delta Lake, or lakehouse architecture. - Preferred: experience working with commercial pharma datasets such as claims, sales, payer, patient, HUB, or specialty pharmacy data.
- Working knowledge of governance and secure data handling practices, including documentation, lineage, and access controls. - Familiarity with BI/visualization tools such as Tableau or Power BI. - Understanding of engineering practices such as Git/version control, code reviews, and basic CI/CD concepts.
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 28, 2026 · today
- Recorded sightings
- 3
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
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Job 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.
Key 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 pharma 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, BI 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 PII/PHI awareness.
Skills & Competencies
- 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 BI, 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 BI/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.
Qualifications & Experience
- 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, 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.
- Preferred: experience with Databricks, Delta Lake, or lakehouse architecture.
- Preferred: experience working with commercial pharma datasets such as claims, sales, payer, patient, HUB, or specialty pharmacy data.
- Preferred: exposure to BI/reporting use cases, semantic layer design, or dashboard-ready data modeling.
We 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.
How We Work
Where 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.
Supporting People with Disabilities
BMS 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 adastaffingsupport@bms.com. Visit careers.bms.com/eeo-accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights
BMS will consider qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.
For 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/
For 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.
Data Protection
We 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.
Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.
If this posting is missing required information required by local law or incorrect, contact BMS at TAEnablement@bms.com with the Job Title and Requisition number. Do not send application-related inquiries to this email. To check your application status, please login to your Candidate Home Account.
Source details
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- Pay
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- Location & working pattern
Hyderabad - TS - IN
How We Work Where 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. Supporting People with Disabilities
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