Data Integration Engineer

AustinWorks is a company focused on building AI infrastructure for the healthcare industry. They are seeking a Data Integration Engineer to design, build, and deploy production-grade data pipelines that transform raw healthcare data into reliable datasets for their AI platform.

Responsibilities:

• Design and build ETL pipelines using PySpark, SQL, Python, and cloud data tools
• Work with large, messy datasets from multiple client systems and transform them into production-ready formats
• Build data validation frameworks to identify schema issues, data quality gaps, transformation errors, and performance bottlenecks
• Troubleshoot complex integration problems across client data sources, internal systems, and production pipelines
• Develop reusable data components and standardized integration patterns
• Optimize distributed data processing workflows for scale and reliability
• Partner with implementation, product, and infrastructure teams to move integrations into production
• Translate partner requirements into clear technical specifications
• Participate in technical conversations with client IT teams around schemas, access methods, and integration constraints
• Document pipelines, transformation logic, and integration patterns

Requirements:

• 5+ years of experience in data engineering, data analytics engineering, solution delivery, or technical implementation
• Strong PySpark experience, ideally working with large-scale distributed data processing
• Advanced SQL skills for querying, transformation, and debugging
• Production ETL experience, including error handling, monitoring, and data quality validation
• Strong Python skills
• Experience working with messy, inconsistent, or multi-source datasets
• Ability to independently diagnose data quality, schema, and pipeline issues
• Strong attention to detail and commitment to reliable production systems
• Clear communication skills and comfort partnering with non-technical or semi-technical stakeholders
• Scrappy, adaptable mindset; able to operate in ambiguous, fast-moving environments
• Experience in consulting, technical implementation, solutions engineering, or forward deployed engineering
• Startup experience, especially at a Series A/B company
• Experience with Databricks or similar distributed data platforms
• Experience with Azure, GCP, or modern cloud data infrastructure
• Healthcare data experience, including EHR, claims, clinical, lab, or imaging data
• Familiarity with Epic Clarity, FHIR, HL7v2, DICOM, LOINC, SNOMED, or ICD-10
• Experience with Azure Databricks, Data Factory, Blob Storage, Delta Lake, Snowflake, or Fabric
• Familiarity with Git, CI/CD, Terraform, or infrastructure-as-code
• Experience with JSON, XML, Parquet, CSV, or other structured/semi-structured data formats