Risevoic
Senior Data Engineer
Company : Adoration Home Health & Hospice
Location : Lexington, KY, 40510
Job Type : Full Time / Part Time
Date Posted : 26 December 2025
Our Company
BrightSpring Health Services
Overview
We are seeking an experienced Senior Data Engineer to join our team in building a next generation AI-enabled Health Cloud Platform. This platform powers intelligent clinical and pharmacy solutions using Generative AI, Agentic AI, Robotic Process Automation (RPA), and Retrieval-Augmented Generation (RAG) with domain-specific vector databases.
As a Senior Data Engineer, you will design and optimize data pipelines, data lakes, and analytics frameworks that enable scalable AI/ML workflows. You will work closely with AI architects, data scientists, and product teams to ensure high-quality, secure, and compliant data infrastructure for healthcare applications.
Responsibilities
- Design, build, and maintain data pipelines for ingesting, transforming, and storing large-scale healthcare datasets.
- Implement ETL/ELT workflows using Databricks, Spark, and Delta Lake for high performance data processing.
- Optimize data architecture for AI/ML workloads, including support for vector databases and RAG pipelines.
- Collaborate with AI teams to integrate structured and unstructured data into predictive and generative AI models.
- Ensure compliance with healthcare data standards (FHIR, HL7, RxNorm) and regulatory requirements (HIPAA).
- Develop and enforce data governance, security, and quality frameworks.
- Monitor and improve data pipeline performance, scalability, and reliability.
- Mentor junior engineers and contribute to best practices in data engineering and MLOps.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
- 10+ years of experience in data engineering with strong expertise in Databricks, Spark, and distributed data systems.
- Proficiency in Python, SQL, and experience with data modeling and data lakehouse architectures.
- Hands-on experience with cloud platforms (Azure preferred; AWS/GCP acceptable).
- Experience with vector databases (FAISS, Weaviate, Pinecone) and RAG pipelines.
- Familiarity with MLOps tools (MLflow, Airflow, or similar) and data versioning.
- Strong understanding of healthcare data standards and compliance frameworks.
- Excellent problem-solving skills and ability to work in a fast-paced, mission-driven environment.
- Knowledge of Generative AI and Agentic AI frameworks (LangChain, AutoGen).
- Familiarity with data security, privacy, and regulatory compliance in healthcare.
- Contributions to open-source projects or experience in large-scale data environments.
- Travel up to 25%
About our Line of Business
BrightSpring Health Services provides complementary home- and community-based pharmacy and provider health solutions for complex populations in need of specialized and/or chronic care. Through the Company’s service lines, including pharmacy, home health care and primary care, and rehabilitation and behavioral health, we provide comprehensive and more integrated care and clinical solutions in all 50 states to over 450,000 customers, clients and patients daily. BrightSpring has consistently demonstrated strong and often industry-leading quality metrics across its services lines while improving the quality of life and health for high-need individuals and reducing overall costs to the healthcare system. For more information, please visit www.brightspringhealth.com. Follow us on Facebook, LinkedIn, and X.Related Jobs
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Frequently asked questions
Senior data engineers in healthcare AI focus on integrating complex medical datasets with cutting-edge AI like generative and agentic models. Their role expands from traditional ETL tasks to optimizing AI-driven pipelines that improve clinical decision-making and pharmacy solutions, reflecting a blend of healthcare compliance and advanced data science techniques.
While senior data scientists typically develop predictive models and algorithms, senior data engineers in Lexington emphasize creating scalable, compliant data infrastructures that support those models. Their expertise lies in pipeline architecture, regulatory adherence, and managing large healthcare datasets essential for AI-powered clinical platforms.
Lexington's healthcare and tech sectors are growing, increasing demand for senior data engineers with AI and compliance experience. Local competition is moderate, with employers favoring candidates skilled in Azure cloud and healthcare data standards, reflecting the city's focus on integrated clinical solutions and specialized care services.
In Lexington, senior data engineers typically earn between $110,000 and $140,000 annually, reflecting regional cost-of-living adjustments. This is slightly below national averages for similar roles in tech hubs, but competitive within healthcare AI due to the blend of specialized skills and compliance expertise required.
Certifications like Azure Data Engineer Associate, HIPAA compliance training, and proficiency with Databricks and Spark are highly valued. Mastery of healthcare data standards (FHIR, HL7) and experience with vector databases enhance employability, aligning with the region’s emphasis on secure, scalable AI-driven healthcare solutions.
Senior data engineers at Adoration Home Health & Hospice build robust data frameworks that enable generative AI to process vast clinical and pharmacy datasets securely. They ensure data pipelines support retrieval-augmented generation and agentic AI, facilitating smarter, compliant healthcare services that improve patient outcomes.
The company seeks experts in Databricks, Spark, Delta Lake, and cloud platforms (preferably Azure), with strong Python and SQL skills. Experience with MLops tools, vector databases, and healthcare data compliance frameworks is crucial to support the AI-driven health cloud platform’s complex, large-scale data orchestration.
Senior data engineers lead architecture design, optimize pipelines for AI workloads, and ensure compliance with health data standards. Juniors typically focus on implementing ETL tasks and data cleaning. Seniors also mentor teams, troubleshoot scalability issues, and collaborate closely with AI scientists to align data strategies.
Vector databases like Faiss or Pinecone enable efficient similarity searches critical for retrieval-augmented generation in AI models. Senior data engineers with this expertise enhance data retrieval speed and accuracy, improving predictive analytics and generative AI outputs, which directly benefits clinical and pharmacy decision systems.