What are the responsibilities and job description for the Data Engineer III position at VCU Health?
We’re seeking a Data Engineer III to help lead the design and evolution of our enterprise data platform in support of both clinical quality improvement and research. In this senior‑level, hands‑on role, you’ll architect and scale modern data pipelines that power analytics, insights, and decision‑making across a complex academic healthcare environment. You’ll take ownership of core data engineering patterns, help define enterprise data standards and strategy, and mentor other engineers—while remaining deeply engaged in building cloud‑based solutions that transform diverse data into trusted assets that advance patient care, operational excellence, and scientific discovery.
The Data Engineer is responsible for designing, developing and maintaining scalable data pipelines and data infrastructure transforming raw data into insights.
Leveraging expertise in data engineering, data management, data operations and governance frameworks, this position will collaborate with cross-functional teams to architect scalable and efficient data pipelines, optimize data storage and retrieval systems, and ensure data quality and integrity throughout the data lifecycle.
Essential Job Statements
Not applicable to this position.
Employment Qualifications
Required Education:
Bachelor’s Degree in Business, IT, Math, Data Analytics, Engineering, or related discipline
Combination of education and experience may be considered in lieu of a degree.
Preferred Education:
Master’s degree in Business, IT, Math, Data Analytics, Engineering or related discipline
Licensure/Certification Required:
Licensure/Certification Preferred:
Minimum Qualifications
Years and Type of Required Experience
8 years of experience in Data Engineering, Data Management or Data Warehouse/Lakehouse design and development.
5 years of experience in Python/PySpark for building and maintaining data pipelines.
3 years of experience with cloud based modern data platforms and services (e.g., Azure, GCP or AWS).
Other Knowledge, Skills And Abilities Required:
Expert knowledge of database systems, data modeling techniques, and SQL proficiency.
Substantial experience creating and enhancing ETL and ELT processes.
Significant experience working with JSON/YAML/XML/Parquet and other open-source data interchange and storage formats.
Experience working with big data technologies like Spark, Kafka, NoSQL DB, Splunk etc.
Significant experience with agile development processes and concepts.
Strong knowledge of DevOps practices and CI/CD processes.
Knowledge of Microservices architecture, Data Product and Data Mesh concepts.
Other Knowledge, Skills And Abilities Preferred:
Displays intellectual curiosity and integrity.
Experience in healthcare environment.
Working Conditions
Physical Requirements
Physical Demands:
Work Position: Sitting
Physical Requirements:
Additional Physical Requirements/ Hazards
Hazards:
Mental/Sensory – Emotional
Mental / Sensory: Strong Recall, Reasoning, Problem Solving, Hearing, Speak Clearly, Write Legibly, Reading, Logical Thinking
Emotional: Fast-paced environment, Able to Handle Multiple Priorities, Frequent and Intense Customer Interactions, Able to Adapt to Frequent Change
Days
EEO Employer/Disabled/Protected Veteran/41 CFR 60-1.4.
The Data Engineer is responsible for designing, developing and maintaining scalable data pipelines and data infrastructure transforming raw data into insights.
Leveraging expertise in data engineering, data management, data operations and governance frameworks, this position will collaborate with cross-functional teams to architect scalable and efficient data pipelines, optimize data storage and retrieval systems, and ensure data quality and integrity throughout the data lifecycle.
Essential Job Statements
- Leads the design and implementation of scalable data pipelines for ingesting, transforming, and loading multi-format, batch or streaming data from various sources into enterprise Data Lakehouse.
- Ensures data quality and integrity through data cleansing, validation, and transformation techniques.
- Automates data processing workflows using scripting languages and orchestration tools.
- Builds and deploys RESTful API’s and web services for data access and data requests.
- Helps and orchestrates the definition of data management strategy and roadmap for the organization.
- Collaborates with data architects, data engineers, and product managers to align data solutions with business strategy.
- Stays current with industry trends, vendor product offerings, and evolving data technologies to ensure the organization leverages the best modern data engineering tools.
- Leads the development and maintenance of technical design documents, coding best practices and standards to ensure consistent and reliable data management processes are in place.
- Responsible for maintaining legacy technologies and processes as new ones are adopted.
- Mentors junior Data Engineers.
Not applicable to this position.
Employment Qualifications
Required Education:
Bachelor’s Degree in Business, IT, Math, Data Analytics, Engineering, or related discipline
Combination of education and experience may be considered in lieu of a degree.
Preferred Education:
Master’s degree in Business, IT, Math, Data Analytics, Engineering or related discipline
Licensure/Certification Required:
Licensure/Certification Preferred:
Minimum Qualifications
Years and Type of Required Experience
8 years of experience in Data Engineering, Data Management or Data Warehouse/Lakehouse design and development.
5 years of experience in Python/PySpark for building and maintaining data pipelines.
3 years of experience with cloud based modern data platforms and services (e.g., Azure, GCP or AWS).
Other Knowledge, Skills And Abilities Required:
Expert knowledge of database systems, data modeling techniques, and SQL proficiency.
Substantial experience creating and enhancing ETL and ELT processes.
Significant experience working with JSON/YAML/XML/Parquet and other open-source data interchange and storage formats.
Experience working with big data technologies like Spark, Kafka, NoSQL DB, Splunk etc.
Significant experience with agile development processes and concepts.
Strong knowledge of DevOps practices and CI/CD processes.
Knowledge of Microservices architecture, Data Product and Data Mesh concepts.
Other Knowledge, Skills And Abilities Preferred:
Displays intellectual curiosity and integrity.
Experience in healthcare environment.
Working Conditions
Physical Requirements
Physical Demands:
Work Position: Sitting
Physical Requirements:
Additional Physical Requirements/ Hazards
Hazards:
Mental/Sensory – Emotional
Mental / Sensory: Strong Recall, Reasoning, Problem Solving, Hearing, Speak Clearly, Write Legibly, Reading, Logical Thinking
Emotional: Fast-paced environment, Able to Handle Multiple Priorities, Frequent and Intense Customer Interactions, Able to Adapt to Frequent Change
Days
EEO Employer/Disabled/Protected Veteran/41 CFR 60-1.4.