Data Engineer I - Transparency Data Operations
Bristol Myers Squibb (company site, opens in a new tab)1–4 yrsHyderabadOn-siteDirect career pageEst. 7–14 LPA
Posted on 28 Sept
Reach people at Bristol Myers Squibb
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Bristol Myers Squibb you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Build and operate end-to-end data pipelines for Transparency Data Operations ensuring accurate, complete, timely, and compliant disclosure of reportable interactions with healthcare entities.
- Monitor data quality, completeness, and timeliness; investigate exceptions and drive remediation with multiple stakeholders globally.
- Support new-market deployments, system changes, platform modernization, data integrations, and automation while maintaining business continuity and process rigor.
Minimum Requirements
- Bachelor's degree in Computer Science, IT, Engineering, Data/Analytics or related field.
- 1-4 years of experience in data engineering, data operations, software development, or related role.
- Proficiency with SQL, Python, ETL/ELT pipelines, databases, cloud data solutions, and operational processes.
- Experience with AWS, Databricks, Oracle/PostgreSQL and Power BI preferred but not mandatory.
Ideal Candidate Profile
- Strong understanding of data ingestion, transformation, validation, reconciliation, exception handling, and controlled data delivery.
- Hands-on experience with SQL, Python, PySpark, Databricks, and AWS cloud components relevant to data engineering.
- Experience working with cross-functional teams and translating regulatory or business requirements into scalable data solutions in a pharmaceutical or healthcare context.