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 and offers a wide variety of competitive benefits, services and programs.
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 experience
SQL, SPARK, and Python proficiency
ELT framework implementation
data modeling and pipeline optimization
collaboration with business stakeholders
version control with Git
Nice-to-have
explaining complex technical information
innovative solution development
familiarity with AI/ML concepts
driving efficiency through architecture
accelerating business decision-making
Key Requirements
4-7 years of analytical engineering, data modeling
Computer Science or related degree preferred
Experience with data engineering tools (AWS, Airflow)
Experience with visualization tools (Tableau, Power BI, Looker)