Jobs at dentsu

Lead quality assurance activities for data warehouse and database projects. Define testing scope, create test plans and SQL scripts, execute functional, regression, load, system, and UAT testing, and manage defect resolution. Investigate data quality issues, validate fixes, communicate test status to clients, establish QA best practices, and mentor a team of QA associates.

Leads end-to-end customer experience research and Voice of Customer programs using quantitative and qualitative methods. Designs NPS, CSAT, and CES measurement frameworks; conducts journey mapping, driver analysis, segmentation, root-cause analysis, and sentiment analysis. Integrates customer feedback with operational data to identify improvement opportunities, then presents prioritized recommendations to senior stakeholders. Manages multiple concurrent projects, budgets, timelines, vendors, and fieldwork partners across products and industries.

Lead Salesforce Marketing Cloud implementations, configure advanced web forms, automations, journeys, data integrations, and campaign processes. Consult with clients on requirements, best practices, adoption, and digital transformation. Build and test campaign solutions, review code, support production platforms, develop Data Cloud segments, and train campaign managers. Collaborate with internal teams to resolve requests and optimize end-to-end campaign delivery.

Lead the architecture and implementation of Salesforce Data Cloud solutions, including data models, ingestion pipelines, identity resolution, activation workflows, and MarTech integrations. Collaborate with marketing, analytics, engineering, and business stakeholders to deliver personalized customer experiences. Ensure data quality, privacy compliance, performance, and troubleshooting across platforms. Mentor engineers, guide technical standards, support segmentation and journey orchestration, and contribute to roadmap planning.

Designs and leads enterprise-scale cloud data platforms and analytics solutions using Snowflake, Python, SQL, and Azure technologies. Responsibilities include data architecture, migration, governance, optimization, and technical leadership. The role also architects generative AI, LLM, and RAG solutions, mentors engineering teams, conducts design reviews, develops roadmaps, and translates business requirements into secure, scalable technical solutions.

Build and maintain cloud data pipelines, transformations, orchestration workflows, governance controls, and analytics-ready datasets. Integrate APIs, Databricks, BI tools, and platform connectors while troubleshooting data quality and performance issues. Collaborate with product, engineering, DevOps, security, and client-facing teams on architecture, access management, infrastructure migrations, documentation, and production support.

Leads the design and implementation of Salesforce Data Cloud solutions, translating business requirements into technical designs, data models, schemas, and ingestion pipelines. Integrates Data Cloud with Marketing Cloud Personalization and other MarTech platforms for audience activation. Manages development teams, ensures delivery quality, troubleshoots complex integrations, supports segmentation and journey orchestration, and drives data governance, privacy, performance, mentoring, and roadmap initiatives.

Lead solution architecture and technical vision for platform teams, mentor engineering leads, ensure scalable resilient microservice-based web applications, drive CI/CD and code quality, collaborate across product, security, DevOps and architecture, and shepherd solutions through governance to meet business requirements.

Lead and scale multi-disciplinary software engineering teams delivering Promotions and Loyalty Services platforms. Own delivery quality, architecture, timelines, KPIs, risk mitigation, client/stakeholder engagement, pre-sales scoping, and people management including hiring and career development.

Lead business transformation strategy for global clients, including major pitches, C-suite engagement, strategic narrative development, consulting frameworks, digital product discovery, user journey mapping, case studies, and proprietary intellectual property. Translate market data and technical insights into transformation roadmaps, support product and engineering teams, and help modernize operating models and grow cross-border revenue. Requires strong consulting, AI and technology literacy, product design, storytelling, marketing attribution, and financial impact measurement expertise.