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Healthcare Data Engineer Jobs in Texas (NOW HIRING)

Data Engineer I

Austin, TX · On-site

$113K - $136K/yr

General Notes The Data Engineer I designs, builds, and maintains scalable healthcare data solutions that support clinical, operational, research, and enterprise analytics initiatives. This role ...

You'll work closely with teammates, engineering partners, and operational stakeholders to ... analysis, data analysis, and/or process improvement. * 2+ years of experience in the healthcare ...

You'll work closely with teammates, engineering partners, and operational stakeholders to ... analysis, data analysis, and/or process improvement. * 2+ years of experience in the healthcare ...

Healthcare Data Project Manager

Austin, TX · On-site

$51.25 - $69.25/hr

This role supports a Technical Project Manager for a data engineering project with an AI adoption ... healthcare data initiatives; familiarity with standards such as FHIR, CCDA, and HL7 is a plus. 10 ...

New

Data Engineer I

Austin, TX · On-site

$113K - $136K/yr

The Data Engineer will be responsible for expanding and optimizing the healthcare system's data architecture and ensuring data quality, security, and accessibility to support clinical and operational ...

Job Title: Healthcare Data Coordinator Pay: $23.00 - $24.00/hr Position Type: Fully On-Site Office Address: 4851 Lyndon B. Johnson Fwy, Suite 1150, Dallas, TX 75244 Overview Altocare is seeking a ...

Data Engineer I

Austin, TX · On-site

$113K - $136K/yr

Purpose The Data Engineer is responsible for expanding and optimizing the healthcare system's data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional ...

Data Engineer- Informatica PowerCenter

Austin, TX · On-site

$52.75 - $69.50/hr

Job Summary (Data Engineer - Informatica PowerCenter, HHSC, State of Texas) - Project Leadership ... healthcare data (PII/PHI). - Adhere to best practices in software development, technical writing ...

Data Engineer

Addison, TX · Hybrid

$110K - $133K/yr

Overview The Data Engineer will play a lead role in acquiring, transforming, and integrating data ... Strong expertise in healthcare data domains is highly preferred. NOTE: THIS IS A HYBRID ROLE. MUST ...

Data Engineer

Addison, TX · Hybrid

$110K - $133K/yr

Overview The Data Engineer will play a lead role in acquiring, transforming, and integrating data ... Strong expertise in healthcare data domains is highly preferred. NOTE: THIS IS A HYBRID ROLE. MUST ...

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Healthcare Data Engineer information

See Texas salary details

$41.5K

$120.9K

$165.4K

How much do healthcare data engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for healthcare data engineer in Texas is $120,851.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,700.00 and $128,100.00 per year, depending on experience, location, and employer.

What is a healthcare data engineer?

A Healthcare Data Engineer is responsible for designing, building, and maintaining data infrastructure in the healthcare industry. They work with large datasets from electronic health records (EHRs), medical devices, and other sources to ensure data is stored, processed, and accessed efficiently. Their role includes developing data pipelines, ensuring compliance with healthcare data regulations (such as HIPAA), and optimizing data for analytics and machine learning. By enabling secure and efficient data management, Healthcare Data Engineers help improve patient care, streamline operations, and support medical research.

What are the key skills and qualifications needed to thrive as a healthcare data engineer, and why are they important?

To thrive as a Healthcare Data Engineer, you need a solid background in computer science, data modeling, and understanding of healthcare data standards, often supported by a relevant degree and experience with big data technologies. Proficiency in programming languages like SQL, Python or R, knowledge of data warehousing solutions, and familiarity with HIPAA regulations or health information systems are typically required, along with certifications such as AWS Certified Data Analytics or Certified Health Data Analyst (CHDA). Strong problem-solving abilities, attention to detail, and effective communication skills are highly valued for collaborating with cross-functional teams. These skills are essential for building secure, reliable data systems that support healthcare analytics and ensure regulatory compliance.

What are some typical projects or challenges a healthcare data engineer might face in their day-to-day work?

As a Healthcare Data Engineer, you may work on projects such as designing data pipelines to aggregate data from multiple EHR systems, ensuring data integrity and security throughout the process. A common challenge in this role is working with complex, sensitive datasets that must remain compliant with healthcare privacy regulations while still being accessible and useful for analysis. You’ll likely collaborate closely with data scientists, clinicians, and IT teams to understand data requirements and optimize system performance. Troubleshooting data quality issues and continuously improving data architecture are regular tasks, making adaptability and continuous learning important for ongoing success.

What are the most commonly searched types of Healthcare Data Engineer jobs in Texas? The most popular types of Healthcare Data Engineer jobs in Texas are:
What are popular job titles related to Healthcare Data Engineer jobs in Texas? For Healthcare Data Engineer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Healthcare Data Engineer jobs in Texas look for? The top searched job categories for Healthcare Data Engineer jobs in Texas are:
What cities in Texas are hiring for Healthcare Data Engineer jobs? Cities in Texas with the most Healthcare Data Engineer job openings:
Infographic showing various Healthcare Data Engineer job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $120,851 per year, or $58.1 per hour.

$113K - $136K/yr

Full-time

Re-posted 23 days ago


University Of Texas at Austin rating

8.2

Company rating: 8.2 out of 10

Based on 63 frontline employees who took The Breakroom Quiz

139th of 615 rated colleges and universities


Job description

Job Posting Title:
Data Engineer I
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Hiring Department:
Dell Medical School
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Position Open To:
All Applicants
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Weekly Scheduled Hours:
40
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FLSA Status:
Exempt from FLSA
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Earliest Start Date:
Immediately
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Position Duration:
Expected to Continue
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Location:
UT MAIN CAMPUS
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Job Details:
General Notes
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.
Important Employment Information
This position is not eligible for employer-sponsored work authorization. Applicants requiring current or future visa sponsorship are not eligible for employment in this position.
Purpose
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.
Responsibilities
Designs and Maintains Data Pipelines
  • Design, build, and maintain scalable data pipeline architecture supporting structured and unstructured healthcare data
  • 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
  • Develop and maintain enterprise data lakes, data warehouses, and data marts utilizing platforms such as Snowflake, Amazon Redshift, or Google BigQuery
  • Configure cloud-based storage and compute environments across AWS, Azure, and Google Cloud Platform
  • Implement schema design, indexing, partitioning, and infrastructure optimization strategies
  • Support high availability, disaster recovery, and business continuity planning

Enables Analytics and Data Science
  • Develop data tools supporting analytics, reporting, and data science initiatives
  • Create reusable components supporting dashboards, reporting, and data products
  • 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

Improves Internal Processes and Scalability
  • Identify, design, and implement internal process improvements
  • Automate manual processes and optimize enterprise data delivery
  • Improve infrastructure scalability, performance, and maintainability
  • Refactor legacy data solutions to improve efficiency
  • Develop and support CI/CD pipelines for data engineering workflows

Collaborates Across Teams
  • Partner with executive leadership, product teams, analysts, software engineers, data scientists, and clinical informatics teams to support enterprise data initiatives
  • Translate business requirements into scalable technical solutions
  • 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

Marginal or Periodic Functions
  • Conduct training sessions supporting enterprise data tools and platforms
  • Participate in vendor evaluations and proof-of-concept initiatives
  • Support data integration activities for organizational growth initiatives
  • Assist with disaster recovery exercises and business continuity planning
  • Support grant-funded research initiatives requiring enterprise data support
  • Perform related duties as assigned

Knowledge, Skills, and Abilities
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

Required 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

Relevant education and experience may be substituted as appropriate.
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

Licenses/Registrations/Certifications
Required
  • None

Preferred
  • AWS Certified Data Analytics
  • Certified Health Data Analyst (CHDA)
  • Project Management Professional (PMP) Certification

Salary Range
$71,060 + depending on qualifications
Working Conditions
  • 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

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

Important for applicants who are NOT current university employees or contingent workers: You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new resume for subsequent applications. Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section, where you may upload multiple files. Before submitting your online job application, ensure that all Required Materials have been uploaded. Once your job application has been submitted, you cannot make changes.
Important for Current University employees and contingent workers: As a current university employee or contingent worker, you must apply within Workday by searching Find UT Jobs. Log in to Workday, navigate to your Worker Profile, click the Career link in the left-hand navigation menu, and update your Professional Profile before applying. This information will be pulled into your application. The application is one page, and you will be prompted to upload your resume. In addition, you must respond to the application questions to upload any additional Required Materials noted above.
Employment Eligibility:
Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers. Staff who are promotion/transfer eligible may apply for positions without supervisor approval.
Retirement Plan Eligibility:
The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.
Background Checks:
A criminal history background check will be required for finalist(s) under consideration for this position.
Equal Opportunity Employer:
The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.
Pay Transparency:
The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information.
Employment Eligibility Verification:
If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented

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