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# Data Engineer (Healthcare)

- **Company:** VeeRteq Solutions Inc
- **Location:** Philadelphia, PA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Microsoft Azure, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Python (Programming Language), Meta-Data Management, Scrum Methodology, Power BI, Azure Data Lake, Azure Data Factory, Sql Optimization, Git, Build Management, Data Lakes, Pyspark, Data Analytics, Apache Kafka, Data Management, Data Lakehouse, Cloud Migration, Terraform, Azure Synapse Analytics, Data Pipelines, Databricks
- **Published:** October 11, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f44af487939ef051

## About the Role

Seeking a Senior Data Engineer with 10+ years of experience to design, build, and lead enterprise-scale data platforms on Azure and Databricks. The role combines hands-on development, solution architecture, technical leadership, and stakeholder management. Experience in Healthcare Payer environments is highly preferred., * Azure Databricks

 * Azure Data Lake Storage (ADLS Gen2)
 * Azure Data Factory (ADF)
 * PySpark
 * Python
 * Advanced SQL
 * Delta Lake
 * Data Lakehouse Architecture
 * Data Modeling
 * ETL/ELT Development
 * Azure Cloud Services
 * Git & CI/CD
 * Agile/Scrum

Preferred Skills:

 * Azure Synapse Analytics
 * Azure Event Hub
 * Kafka
 * Power BI
 * Azure DevOps
 * Terraform
 * Data Governance & Metadata Management
 * Monitoring & Observability Tools
 * AI/ML Data Pipelines

Required Experience:

 * 10+ years in Data Engineering
 * 7+ years with Azure Data Services
 * 5+ years with Azure Databricks
 * Experience leading enterprise cloud data modernization projects

Nice to Have:

 * Healthcare Payer domain experience (strong preference)
 * Experience working directly with business stakeholders and leadership teams.

## Description

* Design and build scalable data platforms, data lakes, and lakehouse solutions.
 * Develop and optimize ETL/ELT pipelines using Azure and Databricks.
 * Lead data architecture, data modeling, and cloud modernization initiatives.
 * Mentor data engineering teams and establish best practices.
 * Improve platform performance, scalability, security, and cost efficiency.
 * Implement CI/CD, monitoring, and production support processes.
 * Collaborate with business leaders, architects, analysts, and product teams.
 * Support analytics, reporting, AI/ML, and data-driven business initiatives.