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

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.

• 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.

• 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.