Senior Data Engineer

Dell Medical School is hiring a Senior Data Engineer in Austin, TX (onsite). This role focuses on designing and optimizing data pipelines and platforms that power enterprise analytics, reporting, and advanced data use cases across clinical, operational, financial, and research domains.

How you’ll make an impact

• Design, build, and maintain complex, scalable ETL/ELT pipelines for structured and unstructured data.
• Lead integration of data from EHRs, financial systems, registries, and external data sources.
• Optimize pipeline performance, reliability, fault tolerance, and cost efficiency.
• Implement batch and near-real-time processing patterns as needed.
• Ensure solutions meet regulatory, privacy, and security requirements, including HIPAA.
• Own specific data platforms or domains (such as clinical analytics and operational reporting) and deliver high-quality outcomes.
• Design and maintain data lake, warehouse, and data mart structures using cloud platforms.
• Build curated, analytics-ready datasets and reusable data assets for analysts and data scientists.
• Partner with data science teams to support feature engineering, model training, and deployment workflows.
• Develop frameworks and patterns that improve self-service analytics and reduce ad hoc data requests.
• Support experimentation and proof-of-concept efforts for predictive analytics and AI/ML use cases.

Responsibilities beyond the pipelines

• Improve data engineering workflows through automation, monitoring, and CI/CD for data pipelines.
• Refactor legacy pipelines and infrastructure to improve maintainability and scalability.
• Establish best practices for code quality, documentation, testing, and version control.
• Evaluate new tools and technologies and recommend adoption when appropriate.
• Serve as a technical mentor to Data Engineer staff, including code reviews and architecture review for quality and consistency.
• Contribute to onboarding, internal training, and knowledge-sharing activities.
• Translate requirements from business, clinical, research, and operational stakeholders into technical solutions.
• Lead data engineering workstreams within cross-functional projects or agile squads.
• Communicate technical concepts, trade-offs, and risks to non-technical audiences.
• Support planning, estimation, and prioritization of data engineering initiatives.
• Assist with data integration for new service lines, acquisitions, or system migrations.
• Participate in vendor evaluations, technical assessments, and disaster recovery testing, including business continuity planning.
• Contribute to grant proposals or research initiatives that require advanced data infrastructure.
• Perform related duties as required.

Required qualifications

• Bachelor’s Degree in Computer Science, Data Engineering, Information Systems, or a related field.
• At least 6 years of experience in data engineering, analytics engineering, or data platform development.
• Demonstrated experience designing and leading complex data pipelines and data platforms.
• Relevant education and experience may be substituted as appropriate.

Technologies you’ll work with

• SQL, Python, Spark, Airflow
• AWS, GCP, Azure/Fabric
• HIPAA, HL7, FHIR

Preferred qualifications

• Master’s Degree in Data Science, Data Engineering, Computer Science, Informatics, or related field.
• Experience in healthcare data engineering or regulated data environments.
• Exposure to AI/ML infrastructure, feature stores, or model operationalization.
• Experience leading technical initiatives or acting as a team lead.

Salary

$138,000+ per year, depending on qualifications.

Working conditions

• Standard office equipment
• Repetitive use of a keyboard
• May be exposed to healthcare-related occupational hazards depending on assignment

Application materials

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