<p>Data Automation Engineer – AI / AWS / Azure</p><p>Work Arrangement: Remote</p><p>Clearance Requirement: Ability to obtain Public Trust</p><p><br></p><p>Position Overview</p><p>We are seeking a highly skilled Data Automation Engineer to design and implement advanced, AI-driven automation solutions across hybrid AWS and Azure environments. This role is focused on building scalable data pipelines, integrating modern cloud services, and leveraging Generative AI technologies to enhance enterprise analytics and operational workflows.</p><p>The ideal candidate is a hands-on engineer with strong expertise in data engineering, cloud platforms, and automation, combined with the ability to innovate and solve complex technical challenges. This role provides the opportunity to work on mission-critical systems, supporting large-scale data processing, reporting, and AI-enabled applications.</p><p><br></p><p>Key Responsibilities</p><p>Data Engineering &amp; Pipeline Development</p><ul><li>Design, build, and maintain scalable data pipelines using AWS services (S3, Glue, Lambda, EMR, DynamoDB)</li><li>Develop and optimize ETL/ELT workflows across hybrid AWS and Azure environments</li><li>Integrate structured, unstructured, and streaming data across enterprise systems</li></ul><p>AI &amp; Automation Engineering</p><ul><li>Leverage Generative AI frameworks (AWS Bedrock, Azure OpenAI, LangChain, Hugging Face) to build intelligent automation</li><li>Implement solutions for embeddings, vector generation, and RAG workflows</li><li>Develop AI-driven tools for data quality, anomaly detection, and pipeline optimization</li><li>Build AI-powered copilots for monitoring, troubleshooting, and workflow automation</li></ul><p>Data Platform Integration &amp; Optimization</p><ul><li>Engineer real-time and batch ingestion pipelines using Spark, Kafka, and Flume</li><li>Integrate enterprise platforms and CRM data into data pipelines for analytics and reporting</li><li>Optimize SQL performance through stored procedures, indexing, and query tuning</li></ul><p>Cloud &amp; DevOps Practices</p><ul><li>Implement CI/CD pipelines using tools such as GitHub, Jenkins, or Azure DevOps</li><li>Develop infrastructure solutions using Infrastructure-as-Code (IaC)</li><li>Ensure cloud security through IAM, RBAC, encryption, and network isolation</li></ul><p>Collaboration &amp; Delivery</p><ul><li>Partner with cross-functional teams to gather requirements and deliver solutions</li><li>Support Agile delivery processes and continuous improvement initiatives</li><li>Provide technical troubleshooting and performance optimization across data systems</li></ul>

<p>Required Qualifications</p><ul><li>Bachelor’s degree in Computer Science or related field</li><li>2+ years of experience in data engineering, automation, or cloud development</li><li>Strong experience with Python and SQL</li><li>Hands-on experience with AWS services (S3, Glue, Lambda, EMR, DynamoDB)</li><li>Experience with data pipeline development and ETL/ELT processes</li><li>Familiarity with Spark, Kafka, Flume, or large-scale data processing</li><li>Exposure to Generative AI / LLM frameworks</li><li>Experience with CI/CD tools and DevOps practices</li><li>Strong troubleshooting, performance tuning, and problem-solving skills</li><li>Ability to obtain Public Trust clearance</li></ul><p>•Preferred Qualifications</p><ul><li>Certifications in AWS, Azure, or Data Engineering disciplines</li><li>Experience implementing RAG pipelines, embeddings, or vector search technologies</li><li>Experience with multi-cloud data integration (AWS ↔ Azure)</li><li>Familiarity with data governance, lineage, and compliance frameworks</li><li>Experience with GenAI-powered developer tools</li><li>Familiarity with Infrastructure-as-Code (Terraform, CloudFormation, Bicep)</li><li>Experience in regulated environments (FedRAMP, HIPAA, etc.)</li></ul><p> Additional Details</p><ul><li>Opportunity to work on cutting-edge AI and automation platforms</li><li>Exposure to enterprise-scale data systems and cloud architectures</li><li>Strong focus on innovation, scalability, and continuous improvement</li></ul>

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