Senior Data Engineer

Position Title:
Senior Data Engineer (Azure Databricks / PySpark)

Location:
Philadelphia, Pennsylvania (100% Remote)

Position Status:
Contract

Pay Rate:
$60/hour on W2

Position Description:

We are seeking a highly skilled
Senior Data Engineer
to support a critical
data engineering initiative within the healthcare operations domain
. This role focuses on building and optimizing scalable data pipelines, enabling advanced analytics, and supporting enterprise data transformation efforts.

The ideal candidate brings strong expertise in
Azure Data Platform technologies, Databricks, PySpark, and data modeling
, along with experience in
workflow orchestration and large-scale data processing
. This is a fully remote opportunity with a fast-moving, collaborative team.

Key Responsibilities:

- Design, develop, and maintain
scalable data pipelines
using
Azure Databricks and PySpark
- Implement and manage
ETL/ELT workflows
using
Azure Data Factory (ADF)
or similar orchestration tools
- Perform
data modeling
to support analytics and reporting use cases
- Optimize data processing for performance, scalability, and reliability
- Collaborate with cross-functional teams to understand data requirements and deliver solutions
- Ensure data quality, integrity, and consistency across systems
- Troubleshoot and resolve complex data and pipeline issues
- Support data integration across multiple systems and platforms
- Document data architecture, pipelines, and workflows
- Contribute to continuous improvement of data engineering best practices

Required Skills/Education:

- 5+ years of experience in
Data Engineering
- Strong hands-on experience with:
- Azure Databricks
- PySpark
- Azure Data Factory (ADF)
or similar orchestration tools
- Solid experience in
data modeling and data architecture
- Experience building and managing
data pipelines and workflow orchestration
- Strong problem-solving and analytical skills
- Excellent communication and collaboration skills
- Experience working in
Agile environments

Preferred Qualifications:

- Experience working in
healthcare data environments
(Epic, clinical, or operational data)
- Familiarity with
large enterprise data platforms
- Experience with
data warehousing and lakehouse architectures
- Exposure to
predictive analytics or advanced analytics platforms