Data Engineer I Full-time

Data Engineer I

The Data Engineer I designs, builds, and maintains scalable healthcare data solutions that support clinical, operational, research, and enterprise analytics initiatives. This role partners with data scientists, analysts, software engineers, and clinical informatics teams to develop secure, reliable, and high-performing data pipelines and infrastructure that enable data-driven decision-making across Dell Medical School and UT Health Austin.

The Data Engineer I is responsible for designing, building, and optimizing healthcare data pipelines and supporting enterprise data infrastructure. This role collaborates with cross-functional teams to develop scalable data solutions, improve data accessibility, ensure data quality, and support analytics, reporting, clinical operations, research, and strategic decision-making across the organization.

• Designs and Maintains Data Pipelines
• Develops and Manages Data Infrastructure
• Enables Analytics and Data Science
• Improves Internal Processes and Scalability
• Collaborates Across Teams
• Ensures Data Governance and Security
• Marginal or Periodic Functions

Technical Learning

• Quickly learn new technologies, cloud platforms, healthcare data standards, and enterprise data engineering tools
• Apply healthcare interoperability standards such as HL7 and FHIR where appropriate
• Maintain current knowledge of cloud platform capabilities and emerging technologies
• Continuously improve technical skills through professional development

Problem Solving

• Diagnose and resolve complex data pipeline and integration challenges
• Design scalable solutions supporting enterprise healthcare data initiatives
• Apply analytical methods to validate data quality and integrity
• Develop practical solutions that improve operational efficiency and system performance

Functional/Technical Skills

• Develop efficient SQL, Python, and other programming solutions supporting enterprise data processing
• Configure cloud infrastructure supporting secure and scalable data workloads
• Design secure, compliant healthcare data architectures
• Build and maintain enterprise data pipelines supporting analytics and reporting

Dealing with Ambiguity

• Adapt effectively to changing priorities, technologies, and organizational needs
• Design flexible data models supporting evolving clinical and operational requirements
• Navigate incomplete or inconsistent data sources while maintaining data quality
• Support multiple concurrent initiatives in dynamic healthcare environments

Collaboration

• Partner effectively with clinicians, analysts, software engineers, and business stakeholders
• Participate in cross-functional Agile development teams
• Build productive working relationships across departments
• Resolve competing technical and operational priorities through collaboration

Strategic Agility

• Design scalable enterprise data solutions supporting future organizational growth
• Align data engineering initiatives with enterprise analytics strategies
• Anticipate technology and regulatory changes affecting healthcare data infrastructure
• Support long-term data architecture and modernization initiatives

• Bachelor's degree in Computer Science, Information Systems, Engineering, Statistics, or a related field
• Minimum of two years of experience in data engineering, data architecture, ETL/ELT development, or a related technical discipline
• Proficiency with big data technologies such as Hadoop, Spark, Kafka, or similar platforms
• Experience working with both SQL and NoSQL databases
• Experience developing and managing data pipelines and workflow orchestration tools
• Experience with AWS services such as EC2, EMR, RDS, Redshift, Glue, and DynamoDB
• Programming or scripting experience using Python, Java, C++, Scala, or similar languages
• Strong analytical, troubleshooting, and problem-solving skills
• Ability to collaborate effectively with cross-functional technical and business teams
• Strong written and verbal communication skills

• Master's degree in Data Engineering, Computer Science, or a related field
• Minimum of five years of experience in healthcare data engineering, analytics, or enterprise data architecture
• Advanced SQL development and relational database experience
• Experience designing, building, and optimizing enterprise data pipelines using Python
• Experience with metadata management, workload orchestration, and data transformation frameworks
• Knowledge of message queuing, stream processing, and scalable cloud-based data storage architectures
• Experience supporting healthcare analytics, clinical data, and enterprise reporting initiatives
• Strong project management and organizational skills

• None
• AWS Certified Data Analytics
• Certified Health Data Analyst (CHDA)
• Project Management Professional (PMP) Certification

$71,060 + depending on qualifications

• Standard office environment and equipment
• Repetitive use of a keyboard and computer
• Hybrid work environment with on-site collaboration as business needs require
• May participate in after-hours support activities for data platform maintenance, deployments, or critical operational initiatives
• May be exposed to communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications, and disoriented or combative patients while supporting healthcare environments

• Resume/CV
• 3 work references with their contact information; at least one reference should be from a supervisor
• Letter of interest