Senior Data Engineer

The Senior Data Engineer role at VeeRteq Solutions Inc. supports healthcare data platforms by designing and operating scalable ETL/ELT and lakehouse solutions built on Google Cloud Platform (GCP). This position focuses on hands-on pipeline development, production support, and healthcare domain data integration.

Location and Work Mode

Irving, TX (hybrid)

Role Summary

As a Senior Data Engineer, you will design, develop, and support GCP-based ETL/ELT pipelines and lakehouse solutions for healthcare data platforms. The work requires practical experience with GCP data technologies and familiarity with healthcare data domains such as Claims, Member, Provider, or Clinical data.

Responsibilities

• Design, develop, and support scalable data pipelines and healthcare data platforms on GCP.
• Build and optimize ETL/ELT pipelines using PySpark, dbt, Dataproc, and Data Composer.
• Develop and maintain data solutions using BigQuery, BigLake, Apache Iceberg, and Starburst.
• Implement healthcare data integrations using APIs, SFTP, and Kafka.
• Design scalable data models and ensure data quality, reliability, and performance.
• Perform data validation, troubleshooting, and performance optimization across data platforms.
• Support production deployments through monitoring, troubleshooting, and issue resolution.
• Implement and maintain data governance, security, and data management best practices.
• Collaborate with architects, data analysts, business stakeholders, and engineering teams.
• Support healthcare data integration and data quality initiatives.
• Contribute to modern lakehouse architecture and large-scale distributed data processing.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Engineering, Data Science, or a related field.
• 8+ years of experience in Data Engineering and Cloud Data Platforms.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Experience building and supporting large-scale healthcare data platforms.
• Experience working with one or more healthcare data domains: Claims Data, Member Data, Provider Data, Clinical Data.
• Understanding of: Healthcare data integration, Healthcare data quality, Data governance, Healthcare data management, and Data security practices.

Technologies

• Google Cloud Platform (GCP), Dataproc, Data Composer
• BigQuery, BigLake, Apache Iceberg, Starburst
• dbt, PySpark, SQL
• ETL/ELT, Kafka, APIs, SFTP

Mandatory Technical Skills

• GCP, BigQuery, BigLake
• Dataproc, Data Composer
• Apache Iceberg, Starburst
• dbt, PySpark, SQL
• ETL/ELT, Kafka
• API Integrations, SFTP
• Data Modeling, Performance Optimization
• Production Monitoring & Troubleshooting

Preferred Qualifications

• Experience with healthcare interoperability standards such as FHIR, HL7, or EDI.
• GCP or other relevant cloud certifications.
• Experience with cloud-native data platforms.
• Experience working in Agile/Scrum delivery environments.
• Experience with modern lakehouse architectures and open table formats.
• Experience with cloud-native monitoring and observability.
• Experience implementing automated data quality practices.
• Experience optimizing large-scale distributed processing and analytical workloads.

Key Competencies

• Data Engineering & Architecture
• GCP Cloud Data Platforms
• Healthcare Data Engineering
• ETL/ELT Development
• Data Modeling
• Performance Optimization
• Data Quality & Governance
• Production Support & Troubleshooting
• Problem Solving & Analytical Skills
• Stakeholder Collaboration