Data Engineer (Data Operations), IQVIA Digital (Remote)

IQVIA is a leading global provider of data, advanced analytics, technology solutions and clinical research services for the life sciences industry. The Data Engineer (Data Operations) is responsible for building, maintaining, and optimizing downstream data pipelines and analytics-ready datasets that power business intelligence and reporting, ensuring high-quality data for analytics teams.

Responsibilities:

• Build and maintain curated data layers and data sources
• Develop and optimize SQL- and Python-based transformations in Snowflake
• Troubleshoot data quality issues originating from upstream pipelines, including identifying root causes and coordinating fixes where needed
• Validate incoming datasets and ensure accuracy, completeness, and consistency before they are surfaced to downstream users
• Design and manage analytics-ready data models and tables to support reporting and dashboards
• Serve as a key point of contact for reporting data layers ensuring data sources meet usability and performance needs
• Monitor data pipelines and datasets for failures, anomalies, and performance issues, and proactively resolve them
• Support production operations, including incident management, backlog prioritization, and SLA adherence
• Partner with upstream engineering teams to escalate and resolve ingestion-related issues, while not owning ingestion directly
• Improve processes for data validation, monitoring, and operational efficiency

Requirements:

• Bachelor's degree
• 3+ years of experience in data engineering, data operations, or backend data development
• Strong hands-on experience with Snowflake (data warehouse design, optimization, and management)
• SQL (advanced querying, performance tuning, and data transformation)
• Python (data processing, scripting, and automation)
• Proven experience building and supporting production-grade data pipelines and workflows
• Strong experience with ETL/ELT tools, orchestration frameworks (e.g., Airflow, Atomic), or similar pipeline management tools
• Experience troubleshooting data issues, pipeline failures, and data inconsistencies, with strong root cause analysis skills
• Solid understanding of data modeling, data warehousing concepts, and data lifecycle management
• Familiarity with CI/CD, version control (Git), and production deployment practices
• Strong problem-solving skills and ability to work independently in fast-paced environments
• Excellent communication skills with the ability to explain data issues and solutions to both technical and non-technical stakeholders
• Experience working with healthcare, pharmaceutical, or life sciences data strongly preferred