Design, develop, and maintain scalable cloud-based data ingestion pipelines and workflows using Google Cloud Platform. Collaborate with engineering teams to troubleshoot production issues and ensure data reliability across enterprise systems.
Understand client businesses and translate their objectives, processes, customer needs, and KPIs into functional requirements, user stories, use cases, and process documentation. Support data analysis, CRM and marketing platform testing, AI use-case discovery, client deliverables, and project coordination with multidisciplinary teams.
Design, build, and maintain production data pipelines and reusable data products to support analytics and AI solutions. Collaborate with cross-functional teams to ensure data reliability, security, and accessibility for enterprise applications.
Design, develop, and implement enterprise integration solutions using the MuleSoft Anypoint Platform. Collaborate with stakeholders to build and maintain APIs and integration flows connecting CRM, ERP, and other enterprise applications.
Design, develop, and maintain production-ready software applications that integrate AI capabilities into enterprise systems and business workflows. Collaborate with cross-functional teams to transform technical requirements into secure, scalable, and maintainable backend services and APIs.
The intern will support the coordination and execution of AI initiatives by organizing project activities, timelines, and documentation. They will also facilitate communication between technical and business stakeholders while contributing to the development and testing of AI-powered solutions.
Design, build, and deploy production-ready GenAI solutions including RAG systems and agentic workflows. Collaborate with cross-functional teams to ensure AI reliability, performance, and scalability in enterprise environments.
Lead business discovery workshops to identify AI opportunities and translate complex business challenges into actionable initiatives. Define business cases, KPIs, and adoption roadmaps while guiding stakeholders through the implementation and validation of business outcomes.
You will lead the technical transition from SAP C4C to Version 2, including architecture design, integration coordination, and data migration strategy. Additionally, you will act as the technical reference for the project, translating business requirements into architecture decisions and managing technical risks.
You will architect and maintain data validation frameworks, testing automation, and quality controls to ensure enterprise data products are accurate and reliable. Additionally, you will collaborate with engineering teams to perform root cause analysis on data discrepancies and integrate quality checks into CI/CD pipelines.
The Business Analyst will bridge business strategy and technical execution by translating strategic goals into actionable requirements for data and analytics initiatives. They will facilitate stakeholder collaboration, manage backlogs, and ensure solutions are aligned with business value throughout the project lifecycle.
The Solution Architect will define and maintain the target-state architecture for enterprise data and analytics platforms while leading discovery and solution design. They will also provide technical leadership throughout the platform lifecycle and mentor engineering teams to ensure alignment with business objectives.
Lead end-to-end enterprise cloud migration and data modernization programs, coordinating business, engineering, analytics, and vendor teams to deliver solutions involving GCP, BigQuery, and Looker. Establish governance and delivery frameworks, manage budgets, risks, resources, and dependencies, and report to executive stakeholders while supporting adoption and business value realization.
You will design smarter marketing processes and workflows by integrating modern marketing tools with AI to create value for organizations. Additionally, you will support daily marketing operations, map digital customer journeys, and collaborate with cross-functional teams to implement technology-driven solutions.
You will co-create and deploy production-ready GenAI and agentic AI solutions by working closely with business and technical stakeholders. Your role involves managing the full lifecycle of AI projects from data qualification and prototyping to monitoring and continuous improvement in client environments.
