Role summary
ASSYST is seeking a Senior Healthcare Data Engineer in Austin, TX (Hybrid) to lead system integration, programming automation, and data modernization. This role involves designing and building automated data pipelines using SAS, Python, R, or SQL to process EHR data, creating rules for record linkage and deduplication, and automating clinical review workflows. The engineer will also build operational dashboards, establish testing frameworks, and ensure data integrity and semantic meaning. Key responsibilities include needs assessment, translating requirements into technical specifications, and maintaining documentation. The role requires 8+ years of experience in scripting, system integration, health/database systems, technical analysis, data validation, and documentation.
ASSYST is seeking an experienced Senior Healthcare Data Engineer to lead system integration, programming automation, and data modernization initiatives for our Client in Austin TX (Hybrid)
The Senior Healthcare Data Engineer leads the effort to evaluate and specify business requirements for electronic initial case report (eICR) ingestion, design auto-population mechanisms for registry fields, streamline the clinical review triage process, and construct operational dashboards. Shall be working closely with epidemiologists, clinical abstractors, and database architects, the developer will build automated, reliable workflows to extract, validate, and incorporate complex clinical and public health data into active surveillance workflows.
Key Responsibilities:
Conduct an in-depth needs assessment to determine system and functional requirements for TBIRDS to ingest incoming eICRs and auto-populate designated registry fields.
Translate epidemiological and clinical surveillance workflows into concrete technical specifications, data dictionaries, and architectural recommendations.
Produce formal System Requirements Documents (SRD) and comprehensive integration runbooks to ensure long-term solution sustainability
Design, build, test, and maintain automated data pipelines using SAS, Python, R, or SQL to extract, ingest, and process high-volume electronic health record (EHR) data feeds.
Create automated rules for deterministic and probabilistic record linkage, entity deduplication, and integration across relational databases.
Automate the clinical review workflow to triage and route incoming case alerts, minimizing manual abstraction lag.
Build, configure, and maintain interactive operational dashboards tracking eCR ingestion volumes, data completeness, processing bottlenecks, and transformation error rates.
Present actionable system and surveillance metrics to branch leadership, epidemiologists, and technical collaborators.
Establish unit, integration, and regression testing frameworks to validate pipeline reliability, data completeness, and standardization.
Ensure transformations strictly preserve semantic meaning across clinical terminology sets and interoperability standards.
Debug script issues, address parsing anomalies, and continuously optimize data ingestion throughput.
Maintain end-to-end documentation for all scripts, schemas, data flows, and automated ETL procedures.
Interface between epidemiological researchers, IT infrastructure teams, and external healthcare reporting partners to ensure aligned system modernization. Qualifications & Skill Requirements
8+ Years in Scripting & Statistical Programming, Hands-on development, testing, maintenance, and troubleshooting using SAS, Python, R, or comparable enterprise data languages.
8+ Years in System Integration & Automation, Proven track record designing automated interoperability workflows, data exchange routines, and dashboard solutions.
8+ Years in Health & Database Systems, Experience querying and managing complex structured or semi-structured healthcare, public health, or administrative datasets using relational databases (SQL).
8+ Years in System Requirements & Technical Analysis, Demonstrated ability to evaluate business and programmatic needs and translate them into formal technical specifications and system reports.
8+ Years in Data Validation & Quality Assurance, Methodological testing, auditing, and verification of automated data integration pipelines.
8+ Years in Technical Documentation & Communication, Strong documentation habits alongside demonstrated ability to explain complex technical concepts to non-technical and clinical staff. Preferred Qualifications
2+ Years in Healthcare Interoperability & Messaging, Direct experience handling electronic case reporting (eCR / eICR), Health Information Exchanges (HIE), Electronic Health Records (EHR), and standards such as HL7 (v2/v3), CDA, HL7 FHIR, XML, or JSON.
2+ Years in Clinical Terminology, Familiarity working with standardized clinical classifications such as SNOMED CT, LOINC, and ICD-10.
2+ Years in Public Health & Registry Systems, Experience working with state public health registries, disease surveillance systems, data linkage/matching methods, and production-grade ETL pipelines. ASSYST is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, disability, military status, national origin or any other characteristic protected under federal, state, or applicable local law
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