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Design, build, and maintain scalable AWS data pipelines and CI/CD for data workflows. Extract and integrate data from SAP HANA, BW, and ABAP. Implement automated deployments, monitor pipelines, resolve incidents, perform root cause analysis, and enforce data governance, security, and performance optimization.

The Senior Data Scientist will lead AI/ML projects, manage a data science team, implement analytical solutions, and leverage data for business insights.

The role involves designing and building data systems using various technologies, especially within Microsoft Azure, and requires experience in system integration and data warehousing.

The Senior Azure Data Engineer will design, develop, and maintain data infrastructure and pipelines, ensuring data quality, integrity, and alignment with business objectives. Responsibilities include collaborating with teams and establishing best practices for data engineering.

Owner of full-stack feature implementation across web, API, cloud, DevOps, and AI-enabled capabilities. Design, build, test, deploy, monitor, and optimize scalable, secure production systems; integrate LLMs and RAG; enforce code quality, mentor juniors, and collaborate with architects, TPMs, product, QA and platform teams.

The Senior Consultant will lead analytics consulting efforts, manage client relationships, develop analytics solutions, mentor a team, and drive project execution across APAC.

Design, build, and maintain Azure-based data infrastructure and pipelines. Implement data models and schemas, ensure data quality, optimize distributed storage and processing (Databricks/PySpark), and establish engineering best practices while partnering with cross-functional teams.

Work with enterprise customers to design, build, and deploy production-grade AI solutions on the Cogentiq platform. Implement integrations with enterprise systems, develop connectors, backend services, and microservices, ensure scalability, security and observability, troubleshoot deployments, and turn deployment learnings into reusable platform capabilities.

Design, implement, and manage GCP-based CI/CD pipelines and platform infrastructure. Automate provisioning with IaC (Terraform/ARM), maintain build/release pipelines, manage Git workflows, integrate automated testing, enforce security best practices, and implement monitoring, logging, and tracing. Collaborate with development and security teams to ensure reliable deployments and platform health.

Lead end-to-end AI solutions for clients, manage project delivery and people, partner with sales for business development, collaborate with engineering/MLOps/DevOps, ensure data quality, model training, tuning, deployment, monitoring, and provide executive updates on status and risks.