Data Engineer (Data Operations)
Rosemont, United States of America | Full time | Home-based | R1518229
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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. This role focuses on data troubleshooting, transformation, and delivery, ensuring that upstream data is validated and converted into reliable, curated data sources for BI and analytics teams. The individual will work hands-on with Snowflake, SQL, and Python to develop data models, resolve data issues, and support production data operations, enabling the BI team to efficiently consume high-quality data through their visualization tools.
Experience with R is a plus, as we transition from R into new technologies.
Essential Functions
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
Qualifications
Bachelor's degree
7+ 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
IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com
IQVIA is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual