Data Engineer I

About the role

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.

Responsibilities

• Designs and Maintains Data Pipelines
• Assemble large, complex datasets that meet functional and non-functional business requirements
• Develop scalable ETL/ELT pipelines utilizing SQL and AWS big data technologies
• Optimize pipeline performance for scalability, latency, throughput, and fault tolerance
• Ensure data pipelines comply with HIPAA and organizational data governance standards
• Develops and Manages Data Infrastructure
• Build infrastructure supporting extraction, transformation, and loading of data from diverse healthcare sources
• Maintain current knowledge of cloud platform capabilities and emerging technologies
• Implement schema design, indexing, partitioning, and infrastructure optimization strategies
• Support high availability, disaster recovery, and business continuity planning
• Enables Analytics and Data Science
• Create data tools supporting analytics, reporting, and data science initiatives
• Build data models and curated datasets for analysts and data scientists
• Enable self-service analytics through standardized datasets and data models
• Collaborate with stakeholders to define key performance indicators (KPIs) and organizational metrics
• Identifies, designs, and implements internal process improvements
• Automate manual processes and optimize enterprise data delivery
• Improve infrastructure scalability, performance, and maintainability
• Refactor legacy data solutions to improve efficiency
• Support cross-functional projects and Agile development teams
• Communicate technical concepts effectively to both technical and non-technical stakeholders
• Mentor junior data engineering team members as appropriate
• Ensures Data Governance and Security
• Support enterprise data governance, security, and regulatory compliance initiatives
• Implement data validation, anomaly detection, and data quality monitoring processes
• Collaborate with data governance teams to enforce organizational standards and policies
• Audit data for completeness, accuracy, consistency, and timeliness
• Support data stewardship and master data management initiatives

Qualifications

• 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

Preferred Qualifications

• 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

Skills

• Technical learning quickly
• Apply healthcare interoperability standards such as HL7 and FHIR
• Continuous improvement of 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
• 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

Benefits

Not specified

Pay

$71,060 + depending on qualifications

Schedule

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