Data Engineer

Enhabit Home Health & Hospice•Dallas, TX

1d•Onsite

About The Position

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and analytics solutions within our Azure Databricks environment. The ideal candidate will have hands-on experience with Apache Spark, Delta Lake, and Azure cloud services, with a strong understanding of healthcare data standards such as HL7, FHIR, or claims data. This role requires a collaborative team player who is comfortable working with clinical and operational stakeholders to deliver reliable, secure, and compliant data solutions in a HIPAA-regulated environment.

Requirements

Bachelor's Degree in Information Systems, Computer Science, Engineering, Statistics, Data Management, or related field
Minimum 5 years of experience in enterprise data engineering.
Hands-on experience building and optimizing data pipelines on Azure Databricks (at least 2+ years)
Proficiency with Delta Lake architecture, including optimization and performance tuning
Experience with Apache Spark (PySpark or Scala) for distributed data processing
Knowledge of Databricks SQL and workflow orchestration
Design and implementation of ETL/ELT processes
SQL proficiency for complex queries and data transformations
Version control (Git) and CI/CD pipeline familiarity
Oral communication, written communication, fluency in English, active listening.
Demonstrated intermediate technology skills. Especially MS office, including word, powerpoint, and excel.
In-office attendance is essential in order to achieve Enhabit objectives, including but not limited to, effective supervision, teamwork, task completion, and other position objectives.

Nice To Haves

Strong understanding of healthcare data standards such as HL7, FHIR, or claims data.

Responsibilities

Build, manage, operate and optimize the data necessary for the enterprise data and analytics initiatives, and for key data and analytics consumers.
Analyze business requirements and architect highly secure, robust, and scalable solutions.
Deliver reliable, secure, and compliant data solutions in a HIPAA-regulated environment.
Design ETL processes to transform raw data into a format suitable for analysis.
Use big data technologies to efficiently process and analyze massive data sets, ensuring infrastructure can handle the demands of modern data workloads.
Drive automation through effective metadata management.
Guarantee compliance with data governance and data security requirements.
Serve as key interface in operationalizing data and analytics on behalf of the business unit(s) and organizational outcomes.
Work with key business stakeholders to plan and deliver optimal analytics and data science solutions.
Complete all other duties as assigned.