Cloud Data Integration and Interoperability Engineer (DevOps Engineer)

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Job Overview

The Cloud Data Integration and Interoperability Engineer at Leidos will be instrumental in designing, implementing, and managing seamless data integration and interoperability solutions in a cloud environment. The engineer will collaborate with cross-functional teams to enhance the performance of data workflows and improve overall system efficiency. Additionally, the role requires a focus on automation, monitoring, and maintenance of data architectures to ensure high availability and reliability while adhering to best practices in DevOps methodologies.

Job Responsibilities

• Design and implement cloud-based data integration solutions to facilitate data flow across various platforms.
• Develop and maintain data pipelines using automation tools to ensure seamless data transfer and processing.
• Collaborate with data scientists and analysts to understand data requirements and provide necessary solutions.
• Monitor and troubleshoot data integration processes to ensure reliable performance and resolve issues proactively.
• Implement best practices for security, compliance, and governance in data handling and integration.
• Create and maintain documentation for data integration workflows, processes, and architectural decisions.
• Assist in the continuous improvement of data management strategies and DevOps practices.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or related field; Master’s degree preferred.
• 4+ years of experience in data integration, data engineering, or DevOps roles.
• Proficiency in cloud technologies such as AWS, Azure, or Google Cloud Platform.
• Experience with ETL tools and data pipeline frameworks such as Apache NiFi, Talend, or Apache Kafka.
• Strong scripting skills in languages such as Python, Bash, or PowerShell.
• Knowledge of containerization technologies (e.g., Docker, Kubernetes) and orchestration tools.
• Familiarity with CI/CD pipelines and DevOps automation tools.
• Excellent problem-solving skills and attention to detail.

Technologies & Tools

This position requires expertise in various technologies and tools, including but not limited to cloud service providers (AWS, Azure, GCP), ETL and data integration tools (Apache NiFi, Talend), programming languages (Python, Bash, PowerShell), containerization (Docker, Kubernetes), and CI/CD tools for automation and deployment strategies.

Ideal Candidates

Ideal candidates for the Cloud Data Integration and Interoperability Engineer position are those who demonstrate a blend of technical proficiency and strong communication skills. They possess an analytical mindset with a keen ability to troubleshoot complex technical challenges. A proactive approach to problem-solving, coupled with a commitment to continuous learning and adapting to new technologies, is essential. Candidates should be team-oriented, able to work collaboratively and efficiently in fast-paced environments, and exhibit a strong understanding of DevOps principles and data management best practices.