Data Engineer - Healthcare

Data Engineer – Healthcare / PHI
Employment Type: Contract
Location: Dallas, TX preferred | Hybrid preferred; remote candidates may be considered
Hourly Rate Range: $50-$65
Start Date: Targeting October/November
Benefits: LaSalle Network consultants are eligible to enroll in benefits. For details, visit  

Position Overview
We are seeking a hands-on Data Engineer to support healthcare and maternal-health data initiatives within a mission-driven organization. This individual will design scalable data models and pipelines, work with healthcare and program subject-matter experts, and translate complex business and data requirements into reliable technical solutions.

The ideal candidate combines strong data-engineering fundamentals with prior exposure to healthcare, PHI, HIPAA-regulated, or other sensitive data environments . This role does not require someone who has independently designed an entire HIPAA compliance framework; rather, we are looking for someone who understands the considerations involved in working with regulated healthcare data and can apply that knowledge within an engineering environment.

Responsibilities

• Design, build, and maintain scalable data models and ETL/ELT pipelines

• Ingest, transform, and integrate healthcare and other complex datasets, including data originating from healthcare/EHR-related systems

• Improve data quality, consistency, reliability, and usability

• Partner with healthcare and program subject-matter experts to understand workflows, terminology, business rules, and data requirements

• Translate healthcare concepts and business processes into technical requirements, data models, and transformation logic

• Develop and maintain data solutions using Databricks, SQL, and Python

• Work with sensitive or regulated data while following established privacy, security, access, and compliance requirements

• Identify data-handling considerations associated with PHI and other regulated information and partner with appropriate stakeholders when additional controls are required

• Troubleshoot complex data issues and recommend sustainable solutions

• Contribute to system design, documentation, development standards, and data-engineering best practices

• Independently manage priorities and take ownership of solutions from discovery through implementation

• Collaborate with internal teams and external engineering resources

Required Qualifications

• Professional experience in data engineering, data modeling, and ETL/ELT development

• Strong hands-on experience with SQL and Python

• Experience working with Databricks or a comparable modern cloud data platform

• Experience designing solutions for complex, heterogeneous, or highly regulated datasets

• Strong understanding of data quality and scalable data-modeling practices

• Ability to independently assess ambiguous business problems and translate them into technical solutions

• Strong communication skills and demonstrated ability to work with nontechnical subject-matter experts

• Ability to operate effectively in a fast-moving environment where requirements may evolve

Preferred Qualifications

• Previous experience working with healthcare data, PHI, HIPAA-regulated data, EHR data, public-health data, or another regulated-data environment

• Experience with PySpark / Spark

• Familiarity with established data privacy, access-control, governance, or de-identification practices

• Experience with GitHub, Git branching, commits, and collaborative version-control workflows

• Experience with modern lakehouse or cloud data architectures

• Experience translating healthcare or other domain-specific business rules into data transformation logic

• Familiarity with AI/LLM-enabled development or data-engineering workflows

Work Environment
This is a small, collaborative organization where engineers have significant ownership over how problems are solved. The individual will frequently partner with subject-matter experts who have deep healthcare or program knowledge but may not be technical data practitioners.

Success in this role requires someone who can learn unfamiliar subject matter quickly, ask effective questions, determine how business concepts should be represented in the data, and independently drive solutions forward rather than relying on fully defined requirements.

Dallas-based candidates who can work in a hybrid environment are preferred, though qualified remote candidates may also be considered.

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