Data Engineer II

Data Engineer II (Mid-Level)

Location: Houston, TX 77070 (Corporate Headquarters)

Job Type: Full-Time | Exempt

Salary: $130,000-$145,000

Schedule: Monday-Friday | Fully Onsite

Build the Future of Healthcare Data

SynergenX Health is transforming healthcare through data, analytics, and artificial intelligence. As we continue to modernize our enterprise data platform, we’re looking for an experienced Data Engineer who thrives in a collaborative environment and enjoys building scalable cloud‑based solutions that directly impact business operations and patient care.

This is an opportunity to work with modern Azure technologies, Databricks, AI‑enabled data engineering, and enterprise analytics while helping mentor junior engineers and influence the future direction of our data platform.

If you’re passionate about solving complex data challenges, building scalable pipelines, and working with cutting‑edge cloud technologies, we’d like to meet you.

As a Data Engineer II, you’ll be responsible for designing, developing, and optimizing enterprise data solutions that support reporting, analytics, artificial intelligence, and operational decision‑making across the organization.

Responsibilities include:

• Design, develop, and maintain enterprise ETL/ELT pipelines using Azure Data Factory and Azure Databricks
• Develop scalable cloud‑native data solutions utilizing Azure Databricks, Delta Lake, and Py Spark
• Build and optimize enterprise data models supporting clinical, financial, and operational analytics
• Develop complex SQL queries, stored procedures, and performance tuning solutions
• Build reusable Python frameworks for automation, orchestration, and data transformation
• Support Azure SQL Database, Azure Synapse Analytics, and Microsoft Fabric environments
• Create datasets and semantic models powering enterprise Power BI reporting
• Build data pipelines supporting Artificial Intelligence (AI), Machine Learning, and advanced analytics initiatives
• Improve data quality, governance, monitoring, and security across enterprise data assets
• Monitor production environments and proactively resolve pipeline and performance issues
• Participate in architecture discussions and contribute to enterprise data platform modernization
• Mentor junior Data Engineers through code reviews, technical guidance, and best practice sharing
• Collaborate with Data Architects, Software Engineers, Business Intelligence Analysts, and business stakeholders to deliver enterprise data solutions
• Stay current on emerging Azure, Databricks, AI, and cloud engineering technologies

• Bachelor’s degree in Computer Science, Information Systems, Software Engineering, Data Engineering, or a related technical field
• 4‑6 years of professional Data Engineering experience
• Hands‑on experience developing production solutions using Azure Databricks
• Strong experience with SQL Server and advanced T‑SQL development
• Strong Python programming experience
• Experience building enterprise ETL/ELT pipelines
• Experience with Azure Data Factory
• Experience working within Azure SQL Database and Azure Synapse Analytics
• Experience with Power BI datasets and enterprise reporting
• Strong understanding of dimensional modeling and data warehouse design
• Experience working with large‑scale cloud data environments
• Ability to mentor junior engineers while remaining hands‑on technically
• Excellent analytical, organizational, and problem‑solving skills
• Fluent English communication skills, both written and verbal, with the ability to communicate effectively across technical and business teams

Experience with any of the following is highly desirable:

• Microsoft Fabric
• Delta Lake
• Py Spark
• Azure Data Lake Storage (ADLS Gen2)
• Azure AI Services
• Azure Machine Learning
• MLflow
• Unity Catalog
• Databricks Workflows
• Azure Dev Ops CI/CD
• Git
• REST APIs
• Healthcare or other highly regulated industries

We’re looking for someone who:

• Has strong production experience with Azure Databricks
• Enjoys building scalable cloud data platforms
• Understands how modern data engineering enables AI and machine learning initiatives
• Can independently solve complex technical problems
• Takes ownership of projects…