This role bridges the gap between data engineering and data analytics, focusing on transforming raw data into structured, business-ready datasets
Job Summary
This role bridges the gap between data engineering and data analytics, focusing on transforming raw data into structured, business-ready datasets.
The ideal candidate will be responsible for designing, developing, and implementing analytical workflows, ensuring that data is clean, well-modeled, and optimized for business intelligence and decision-making.
Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives.
Matching Summary
This role bridges the gap between data engineering and data analytics, focusing on transforming raw data into structured, business-ready datasets.
Skills & Requirements
Must-have
dbt and Databricks
SQL, SPARK and Python
data transformation and modeling
ELT framework
AWS, Airflow knowledge
Git, SVN experience
Nice-to-have
innovative solutions
explain complex technical information
AI and ML collaboration
Agile development
self-service analytics enablement
Key Requirements
4-7 years of analytical engineering, data modeling
Computer Science, Physics, Math, Data Science, Pharmaceutical Science, or Engineering degree