Cloud Data Engineer Lead Specialist

Job Title: Cloud Data Engineer Lead Specialist Location: Durham, North Carolina Experience Required: 12+ Years Employment Type: Contract Interview Type: In-Person or Webcam Job Description We are seeking an experienced Cloud Data Engineer Lead Specialist to design, develop, and optimize secure, scalable cloud-based data solutions. This role involves leading data engineering initiatives, building modern data platforms, and implementing advanced data pipelines across cloud environments. The ideal candidate will have extensive hands-on expertise in cloud data ecosystems, large-scale data processing, and enterprise integration, along with a strong technical leadership background. Key Responsibilities Lead the architecture, design, and implementation of cloud-based data platforms and data pipelines. Develop and maintain large-scale ETL/ELT processes that support business analytics and reporting. Build and optimize data ingestion, transformation, and storage frameworks for structured and unstructured data. Ensure data quality, governance, security, and compliance across cloud and hybrid data environments. Evaluate new cloud technologies, tools, and methodologies to improve data engineering capabilities. Lead a team of data engineers, provide mentoring, and oversee delivery execution. Collaborate with stakeholders including data architects, analysts, DevOps, and business users. Improve data processing performance and reliability through monitoring, automation, and best practices. Troubleshoot and resolve complex data pipeline or infrastructure issues in production environments. Participate in architecture reviews, design sessions, and solution planning meetings. Required Skills and Qualifications 12+ years of professional experience in data engineering and large-scale enterprise data solutions. Strong hands-on experience with at least one major cloud platform (AWS, Azure, or Google Cloud Expertise in cloud-native data services such as AWS Glue, Lambda, S3, EMR, Redshift, Lake Formation, Azure Synapse, Data Factory, Databricks, or BigQuery. Advanced knowledge of SQL, Python, Spark, PySpark, and distributed data frameworks. Proven background in building ELT/ETL systems and high-performance batch and streaming pipelines. Experience with data warehousing and data lake design concepts. Strong understanding of CI/CD practices, DevOps, and infrastructure-as-code tools (Terraform, CloudFormation, etc. Knowledge of data security, access control, and governance standards. Excellent communication, leadership, and problem-solving skills. Experience working in Agile development environments.