Senior GCP Data Engineer

We are an AI-led, platform-driven Digital Engineering and Enterprise Modernization partner, combining deep technical expertise and industry experience to help our clients anticipate what's next. Our offerings and proven solutions create a unique competitive advantage for our clients by giving them the power to see beyond and rise above. We work with many industry-leading organizations across the world, including 18 of the Fortune 50 companies, 7 of the 10 top US banks, 9 of the 10 technology companies, and numerous innovators across the healthcare ecosystem.

Our disruptor's mindset, commitment to client success, and agility to thrive in the dynamic environment have enabled us to sustain our growth momentum. Persistent has been recognized across top industry platforms for innovation, leadership, and inclusion. We have delivered 26sequential quarters of growth with $487.6M in Q4 FY26 revenue, up 7.8% Q-o-Q and 20.0% Y-o-Y. Our 29,500+global team members, located in 21 countries, have been instrumental in helping the market leaders transform their industries.

We received five awards at the ISG (Information Services Group) Provider Lens Awards 2026 and, for the second year in a row, were awarded the Growth Honor of the Year at the Everest Group Elevate 2026.

We are seeking a highly skilled Senior GCP Data Engineer with strong expertise in Google Cloud Platform, Big Query, Dataflow, and modern data integration technologies. The ideal candidate will be responsible for designing, building, and optimizing scalable data pipelines while ensuring high performance, reliability, and data quality across enterprise data platforms. Experience with Starburst and/or Dremio is mandatory for enabling data virtualization, query federation, and analytics across distributed data sources.

• Location:
  Charlotte, NC
• Experience: 7 to 12 Years
• Job Type: Contract

• Design, develop, and deploy AI agents using Python, Lang Graph, Microsoft Agent Framework, and Azure OpenAI.
• Build and optimize Survey Programming Agents covering Questionnaire Parsing, Routing Logic, JSON Generation, Dimensions Setup, STG Generation, Translation Workflows, DMS Script Creation, Link Testing, Survey Quality Control, and Change Impact Analysis.
• Design, develop, and deploy scalable ETL/ELT data pipelines using Python and GCP-native services.
• Build and maintain enterprise-grade data integration solutions across multiple data sources and platforms.
• Integrate MongoDB data into Google Cloud Storage and Big Query environments.
• Design and optimize data ingestion, transformation, and analytical processing workflows.
• Develop and support data virtualization and federated query solutions using Starburst and/or Dremio.
• Optimize Big Query workloads through partitioning, clustering, query tuning, and performance engineering.
• Monitor and troubleshoot production data pipelines and resolve data quality issues.
• Perform debugging, root cause analysis, and issue resolution for data processing failures.
• Optimize Dataflow jobs and MongoDB indexing strategies to improve performance and reduce operational costs.
• Implement monitoring, alerting, and operational support processes for data platforms.
• Collaborate with Data Scientists, Software Engineers, Architects, and business stakeholders to deliver reliable data solutions.
• Develop and maintain technical documentation, operational runbooks, and deployment procedures.
• Implement CI/CD processes for data engineering solutions and cloud deployments.
• Ensure adherence to data governance, security, compliance, and operational best practices.

• 7-12 years of experience in Data Engineering, Cloud Data Platforms, or Big Data environments.
• Strong hands-on experience with Google Cloud Platform (GCP).
• Expertise in Big Query, Cloud Dataflow, Cloud Composer (Apache Airflow), and Cloud Storage.
• Mandatory hands-on experience with Starburst and/or Dremio.
• Strong experience implementing ETL/ELT pipelines and enterprise data integration solutions.
• Advanced Python programming and scripting expertise.
• Strong SQL development skills and query optimization experience.
• Experience working with MongoDB and No
  
  SQL database technologies.
• Solid understanding of data warehousing, dimensional modeling, and analytical data platforms.
• Hands-on experience monitoring and supporting production-grade data environments.
• Experience with Cloud Logging, Cloud Monitoring, and incident troubleshooting.
• Knowledge of CI/CD implementation and Dev Ops practices for data…