Senior Data Engineer

The Senior Data Engineer at Dell Medical School is responsible for designing, developing, and optimizing complex data pipelines and platforms that enable enterprise analytics, reporting, and advanced data initiatives. This role also provides technical mentorship and leads delivery across clinical, operational, financial, and research data domains.

Key Responsibilities

• Designs, builds, and maintains complex, scalable ETL/ELT pipelines for structured and unstructured data.
• Leads integration of data from EHRs, financial systems, registries, and external data sources.
• Optimizes pipelines for performance, reliability, fault tolerance, and cost efficiency.
• Implements batch and near-real-time processing patterns as needed.
• Ensures pipelines meet regulatory, privacy, and security requirements, including HIPAA.
• Acts as technical owner for specific data platforms, domains, or subject areas, such as clinical analytics and operational reporting.
• Designs and maintains data lake, warehouse, and data mart structures using cloud platforms.
• Develops and enforces data modeling standards, including schema design and partitioning strategies.
• Partners with IT and cloud teams to support availability, scalability, and disaster recovery readiness.
• Builds curated, analytics-ready datasets and reusable data assets for analysts and data scientists.
• Collaborates with data science teams on feature engineering, model training, and deployment workflows.
• Develops frameworks and patterns that improve self-service analytics and reduce ad hoc data requests.
• Supports experimentation and proof-of-concept work for predictive analytics and AI/ML use cases.
• Improves data engineering workflows through automation, monitoring, and CI/CD for data pipelines.
• Refactors legacy pipelines and infrastructure to enhance maintainability and scalability.
• Establishes best practices for code quality, documentation, testing, and version control.
• Evaluates new tools and technologies and recommends adoption where appropriate.
• Mentors Data Engineer staff, including reviewing code, pipeline designs, and architecture artifacts for quality and consistency.
• Provides guidance on complex technical problems and supports onboarding, internal training, and knowledge-sharing.
• Partners with business, clinical, research, and operational stakeholders to translate requirements into technical solutions.
• Leads data engineering workstreams within cross-functional projects or agile squads.
• Communicates technical concepts, trade-offs, and risks to non-technical audiences.
• Supports planning, estimation, and prioritization of data engineering initiatives.
• Supports data integration efforts for new service lines, acquisitions, or system migrations.
• Participates in vendor evaluations and technical assessments.
• Assists with disaster recovery testing and business continuity planning.
• Contributes to grant proposals or research initiatives requiring advanced data infrastructure.
• Performs 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

• 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.

Licenses, Registrations, or Certifications

Required: None

Preferred Certifications

• Cloud Certification
• Microsoft Certified: Azure Data Engineer Associate
• Google Cloud Professional Data Engineer
• AWS Certified Data Analytics – Specialty

Compensation

Salary range: $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

Location

Austin, TX (onsite)

Required Application Materials

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