Manager, Data and AI Analytics
Bristol Myers Squibb
June 28, 2026
Remote friendly (Seattle, WA)
United States
IT
Position Summary:
The Manager, Data & AI Analytics Engineering is a hands-on individual contributor responsible for designing, building, and delivering scalable data and AI-driven analytics solutions supporting Global Patient Operations (GPO).
Key Responsibilities:
- Collaborate with cross-functional teams to translate business needs into scalable data solutions.
- Design, develop, and maintain scalable ETL pipelines and data models using SQL, Python, dbt, and Databricks (Medallion architecture: bronze/silver/gold).
- Build and optimize complex SQL transformation pipelines integrating data from SAP, Oracle, Salesforce, AWS Athena, PostgreSQL, and other enterprise systems.
- Develop curated datasets and semantic models for the GPO Analytics Hub and enterprise reporting.
- Design/optimize Power BI and Tableau datasets/dashboards for consistent KPI reporting and executive analytics.
- Standardize KPIs, definitions, and data logic across GPO.
- Enable AI/automation initiatives (predictive analytics, Copilot, agent-based solutions).
- Build data harmonization/reconciliation pipelines; reusable ETL orchestration/API integration frameworks with validation and alerting.
- Implement data quality checks, monitoring, and production-ready deployment; optimize performance across PostgreSQL, Impala/Cloudera, and Athena.
- Lead requirements gathering, UAT, stakeholder reviews, and production rollouts; maintain documentation/metadata/lineage.
- Provide technical leadership, code reviews, and best practices (no direct reports).
Key Qualifications & Experience:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Analytics, or related field.
- 8+ years in data engineering or analytics engineering.
- Strong hands-on SQL and Python; experience in large-scale data environments.
- Databricks, dbt, and cloud platforms (AWS/Azure); ETL/data model/semantic layer experience.
- Power BI and/or Tableau experience.
- AI/ML workflow understanding; life sciences/pharmaceutical/regulated environment experience.
- Hands-on GenAI/LLMs/agent-based AI; Data Ops, CI/CD, Git-based workflows.
- Familiarity with Domino Data Lab; knowledge of data governance/metadata/lineage.
Benefits (explicitly stated):
- Health coverage (medical, pharmacy, dental, vision).
- Wellbeing support programs and EAP.
- 401(k), disability and life insurance, and additional protections.
- Paid Time Off: flexible time off (unlimited with manager approval) and national holidays (specific variants by location/role).
Application Instructions:
- None specified in the job description text provided.
The Manager, Data & AI Analytics Engineering is a hands-on individual contributor responsible for designing, building, and delivering scalable data and AI-driven analytics solutions supporting Global Patient Operations (GPO).
Key Responsibilities:
- Collaborate with cross-functional teams to translate business needs into scalable data solutions.
- Design, develop, and maintain scalable ETL pipelines and data models using SQL, Python, dbt, and Databricks (Medallion architecture: bronze/silver/gold).
- Build and optimize complex SQL transformation pipelines integrating data from SAP, Oracle, Salesforce, AWS Athena, PostgreSQL, and other enterprise systems.
- Develop curated datasets and semantic models for the GPO Analytics Hub and enterprise reporting.
- Design/optimize Power BI and Tableau datasets/dashboards for consistent KPI reporting and executive analytics.
- Standardize KPIs, definitions, and data logic across GPO.
- Enable AI/automation initiatives (predictive analytics, Copilot, agent-based solutions).
- Build data harmonization/reconciliation pipelines; reusable ETL orchestration/API integration frameworks with validation and alerting.
- Implement data quality checks, monitoring, and production-ready deployment; optimize performance across PostgreSQL, Impala/Cloudera, and Athena.
- Lead requirements gathering, UAT, stakeholder reviews, and production rollouts; maintain documentation/metadata/lineage.
- Provide technical leadership, code reviews, and best practices (no direct reports).
Key Qualifications & Experience:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Analytics, or related field.
- 8+ years in data engineering or analytics engineering.
- Strong hands-on SQL and Python; experience in large-scale data environments.
- Databricks, dbt, and cloud platforms (AWS/Azure); ETL/data model/semantic layer experience.
- Power BI and/or Tableau experience.
- AI/ML workflow understanding; life sciences/pharmaceutical/regulated environment experience.
- Hands-on GenAI/LLMs/agent-based AI; Data Ops, CI/CD, Git-based workflows.
- Familiarity with Domino Data Lab; knowledge of data governance/metadata/lineage.
Benefits (explicitly stated):
- Health coverage (medical, pharmacy, dental, vision).
- Wellbeing support programs and EAP.
- 401(k), disability and life insurance, and additional protections.
- Paid Time Off: flexible time off (unlimited with manager approval) and national holidays (specific variants by location/role).
Application Instructions:
- None specified in the job description text provided.