GCP Data Engineer

Position Title: GCP Data Engineer Location: Charlotte, NC (Hybrid – Local Candidates Only) Visa Status: No Sponsorship Available Interview Process: Onsite Interview Important Requirements • Candidates must currently reside in the Charlotte, NC area. • No relocation candidates will be considered. • Candidates must have prior Financial Services / Banking / Capital Markets experience. • Strong communication and stakeholder management skills are required. Position Overview We are seeking an experienced GCP Data Engineer to join a high-performing data engineering team supporting critical data initiatives within a leading Financial Services organization. The ideal candidate will have deep expertise in building scalable cloud-native data solutions on Google Cloud Platform (GCP), strong hands-on development experience with Python, SQL, PySpark, and Airflow, and the ability to contribute to enterprise-level data architecture and design. This role requires a strong understanding of large-scale data processing, cloud data platforms, ETL/ELT frameworks, data modeling, orchestration, and data architecture within highly regulated financial environments. Required Skills & Experience Must-Have Technical Skills • 8+ years of Data Engineering experience. • 4+ years of hands-on experience with Google Cloud Platform (GCP). • Strong expertise in: • Python • SQL • PySpark • Apache Airflow • Experience designing and implementing enterprise-scale data pipelines and frameworks. • Strong understanding of data architecture, data modeling, and cloud-native data solutions. • Experience with large-scale batch and real-time data processing. • Hands-on experience with: • BigQuery • Cloud Storage • Dataproc • Cloud Composer (Airflow) • Pub/Sub • Dataflow (preferred) • Experience working with structured, semi-structured, and unstructured datasets. • Strong performance tuning and optimization experience for large data workloads. Financial Services Experience (Required) • Previous experience supporting Banking, Financial Services, Capital Markets, Wealth Management, or Insurance clients. • Understanding of financial data domains, regulatory requirements, governance, and data quality standards. Key Responsibilities • Design, develop, and maintain scalable data pipelines on GCP. • Build and optimize ETL/ELT processes using Python, PySpark, SQL, and Airflow. • Develop cloud-native data solutions leveraging GCP services. • Collaborate with business stakeholders, architects, and application teams to define data requirements. • Design and implement robust data architecture frameworks and best practices. • Ensure data quality, integrity, governance, security, and compliance standards are met. • Perform data modeling and optimize data structures for analytics and reporting. • Monitor, troubleshoot, and improve performance of data platforms and pipelines. • Participate in architecture discussions and provide technical leadership on cloud data initiatives. • Support CI/CD, automation, and DevOps practices for data engineering workloads. Preferred Qualifications • Experience with real-time streaming technologies and event-driven architectures. • Knowledge of data governance and metadata management tools. • Experience with Terraform or Infrastructure as Code (IaC). • Exposure to data warehousing and analytics platforms. • GCP Professional Data Engineer Certification preferred. • Experience working in Agile/Scrum environments.