Senior Healthcare Data Engineer

Description

The company is hiring a senior healthcare data engineer to lead system integration, automation and data modernization for its client in Austin, TX. The role is hybrid.

You will assess requirements for ingesting electronic initial case reports (eICR), design auto-population for registry fields, streamline clinical review triage and build operational dashboards. You will work with epidemiologists, clinical abstractors and database architects to build automated, reliable workflows that pull in, check and use complex clinical and public health data in active surveillance.

Responsibilities

• Run a detailed needs assessment to define the system and functional requirements for TBIRDS, covering eICR ingestion and auto-population of designated registry fields.
• Turn epidemiological and clinical surveillance workflows into technical specifications, data dictionaries and architecture recommendations.
• Write formal System Requirements Documents (SRD) and thorough integration runbooks so the solution stays sustainable over time.
• Build, test and maintain automated pipelines in SAS, Python, R or SQL that extract, ingest and process high-volume electronic health record (EHR) feeds.
• Write automated rules for deterministic and probabilistic record linkage, entity deduplication and cross-database integration.
• Automate clinical review so incoming case alerts are triaged and routed with less manual abstraction delay.
• Build, configure and maintain interactive operational dashboards that track eCR volumes, data completeness, processing bottlenecks and transformation error rates.
• Present useful system and surveillance metrics to branch leadership, epidemiologists and technical colleagues.
• Set up unit, integration and regression testing to confirm pipeline reliability, completeness and standardization.
• Make sure transformations keep the meaning of clinical terminology and interoperability standards intact.
• Debug scripts, handle parsing anomalies and keep improving ingestion throughput.
• Keep end-to-end documentation current for all scripts, schemas, data flows and automated ETL procedures.
• Liaise between epidemiological researchers, IT infrastructure teams and external healthcare reporting partners to keep modernization aligned.

Requirements

• 8+ years of scripting and statistical programming, including developing, testing, maintaining and troubleshooting in SAS, Python, R or similar enterprise data languages.
• 8+ years of system integration and automation, with a proven record of designing interoperability workflows, data exchange routines and dashboards.
• 8+ years working with complex structured or semi-structured healthcare, public health or administrative data in relational databases using SQL.
• 8+ years turning business and program needs into formal technical specifications and system reports.
• 8+ years of data validation and quality assurance, including methodical testing, auditing and verification of automated integration pipelines.
• 8+ years of technical documentation and communication, with a record of explaining complex concepts to non-technical and clinical staff.
• Preferred: 2+ years with healthcare interoperability and messaging, including electronic case reporting (eCR/eICR), Health Information Exchanges (HIE), EHRs and standards such as HL7 (v2/v3), CDA, HL7 FHIR, XML or JSON.
• Preferred: 2+ years working with clinical classifications such as SNOMED CT, LOINC and ICD-10.
• Preferred: 2+ years with public health and registry systems, including state registries, disease surveillance systems, data linkage and matching methods, and production ETL pipelines.

Conditions

Hybrid role based in Austin, TX.

Equal opportunity employer.