Jobs at Metyis

Lead client data governance implementation by identifying stakeholders and governance gaps, defining ownership and decision forums, facilitating business-technical workshops, and embedding governance into daily operations. The role translates ambiguous challenges into actionable approaches, develops reusable templates and playbooks, and collaborates with data, analytics, architecture, privacy, and security specialists. It requires stakeholder engagement, data governance or related experience, data platform understanding, and strong communication skills.

Lead client data governance implementation by identifying governance gaps, defining ownership roles, facilitating stakeholder workshops, translating ambiguous challenges into actionable approaches, and embedding governance into daily operations. Develop reusable templates, playbooks, and implementation accelerators while collaborating with data, analytics, architecture, privacy, security, and business consulting specialists.

Designs and governs scalable AI architecture across cloud, data, and application environments. Responsibilities include defining architectural standards, advising on AI solution design, overseeing integrations and deployments, monitoring infrastructure performance and costs, coordinating technical stakeholders, supporting specifications and acceptance testing, and mitigating technical risks. The role requires hands-on experience with cloud platforms, AI/ML systems, DevOps, data architecture, containers, CI/CD, infrastructure as code, and monitoring.

Lead the architecture, integration, scalability, reliability, and governance of enterprise AI systems. Establish technical standards, advise on AI solution design, oversee specifications and testing, manage cloud infrastructure performance and costs, coordinate cross-functional teams, and mitigate technical risks. The role requires strong experience in DevOps, cloud architecture, AI tooling, data platforms, infrastructure as code, CI/CD, containers, and major cloud providers.

Support the development, testing, deployment, and monitoring of AI solutions and products. Prepare data and knowledge foundations, including data sources, knowledge bases, and RAG pipelines. Assist with prompt engineering, context strategies, AI agents, orchestration workflows, and experimentation with emerging models and tools. Translate business needs into practical AI use cases, document solutions, and collaborate with technical and business stakeholders.

Support the development, testing, deployment, and monitoring of AI solutions and products. Help prepare data foundations, knowledge bases, and RAG pipelines; test prompts and context strategies; research AI models and frameworks; and contribute to AI agents and orchestration workflows. Translate business challenges into practical AI use cases, document experiments and methodologies, and collaborate with technical and business stakeholders to improve AI application performance.

Support the development, testing, deployment, and improvement of AI solutions, including LLM applications, RAG pipelines, prompts, AI agents, and orchestration workflows. Prepare data and knowledge foundations, research emerging models and frameworks, translate business needs into AI use cases, monitor solution performance, and document methodologies. Collaborate with senior technical professionals, data teams, and business stakeholders in an international environment.

Design and support scalable AI infrastructure, applications, data pipelines, and cloud-based solutions. Collaborate with technical and business stakeholders, contribute to architecture and documentation, support deployments and testing, monitor performance and costs, troubleshoot issues, and help manage technical risks. The role requires cloud, DevOps, data engineering, infrastructure-as-code, containerization, CI/CD, monitoring, and AI/ML platform experience.

Supports the development, testing, deployment, and monitoring of AI solutions. Responsibilities include preparing data and knowledge foundations, building RAG pipelines, testing prompts and context strategies, researching AI models and tools, contributing to AI agents and orchestration workflows, translating business needs into use cases, and documenting solutions. The role collaborates with data, AI, technical, and business teams while continuously improving AI application performance and reliability.

Design and deploy AI solutions from prototype to production. Build knowledge graphs, ontologies, governance frameworks, data lineage systems, and RAG pipelines. Apply prompt, context, memory, and harness engineering; translate business needs into AI workflows; contribute to agentic AI orchestration; evaluate emerging models and tools; and document reusable standards and assets. Collaborate with data teams and business stakeholders in an international fashion technology environment.

Lead a data engineering team and technical roadmaps for client data platforms. Design architectures and deliver scalable ETL/ELT pipelines, data lakes, warehouses, analytics products, APIs, dashboards, and data insights using Python, Spark, and Azure. Ensure engineering excellence, automated testing, governance, and alignment with digital standards. Collaborate with data scientists, stakeholders, and project teams, while coaching team members and evaluating business needs.

Maintain and develop Linux-based server environments, administer Centreon monitoring infrastructure, and build configuration management and deployment pipelines. Responsibilities include onboarding systems, writing Python and Bash check scripts, integrating monitoring and performance metrics, troubleshooting faults, optimizing and hardening systems, documenting operations, and improving processes. The role requires strong Linux, Centreon, automation, networking, Git, and CI/CD expertise.

Design, build, and refine AI solutions from prototype through production. Develop context layers using knowledge graphs, ontologies, governance, data lineage, and RAG architectures. Apply prompt, context, memory, and harness engineering; translate business challenges into AI workflows; contribute to agentic systems and orchestration architectures; evaluate emerging AI tools; and document reusable methodologies and standards.

Design, build, deploy, and refine AI solutions across the full lifecycle. Develop knowledge graphs, ontologies, governance and lineage frameworks, RAG pipelines, prompt and context engineering practices, and agentic AI orchestration systems. Translate business challenges into AI workflows, evaluate emerging AI technologies, document reusable standards, and collaborate with data teams and business stakeholders.

Perform data analysis across growth revenue management, marketing, customer lifecycle, CRM, and risk analytics. Use statistical and programming tools to acquire, clean, integrate, analyze, interpret, and visualize data. Develop hypotheses and actionable recommendations, present findings, facilitate workshops, manage executive stakeholders, and mentor team members.

Perform data analysis across growth revenue management, marketing, CRM, customer lifecycle, and risk analytics. Use statistical and programming tools to clean, analyze, interpret, and visualize data; develop hypotheses and actionable recommendations; present findings; facilitate workshops; manage executive stakeholders; and mentor team members.

Build scalable data engineering solutions for digital marketing, e-commerce, business intelligence, and self-service analytics. Responsibilities include designing ETL/ELT pipelines, data lakes, anonymization workflows, streaming hubs, web services, and machine learning model pipelines. The role involves requirements gathering, client collaboration, mentoring, technical training, and contributing to Big Data strategies using Azure, Airflow, Kubernetes, Python, and related technologies.

Perform data analysis across growth revenue management, marketing, CRM, and risk analytics using statistical and programming tools. Clean, integrate, interpret, and visualize data; develop hypotheses and actionable recommendations; present findings to stakeholders and executives; facilitate workshops; and coach team members.

Provide hands-on IT and workplace support for laptops, mobile devices, meeting rooms, Microsoft 365, connectivity, and collaboration technologies. Manage Windows and macOS devices through Intune and Autopilot, support iOS and Android device management, oversee hardware lifecycle activities, and administer onboarding and offboarding. Serve as the primary IT contact for the Gurgaon office, maintain technical documentation, and collaborate with technology partners on modernization, automation, cloud, and security initiatives.

Lead complex programmes and portfolios involving multidisciplinary teams, technology, data, digital commerce, and business transformation. Responsibilities include defining governance and delivery strategies, managing budgets, risks, dependencies, resources, vendors, and benefits, and reporting to executive stakeholders. The role leads project managers, facilitates steering committees, supports client growth and business development, and drives delivery excellence, organizational transformation, and measurable business outcomes. International travel is required as needed.