Jobs at Dentsu Creative

Lead the design, development, optimization, and support of scalable data engineering and database marketing solutions. Build and maintain ETL/ELT pipelines using Azure Data Factory, Databricks, and related technologies; create technical designs; troubleshoot production issues; conduct code reviews; and ensure performance, quality, and documentation standards. Collaborate with clients and internal stakeholders, manage small project teams, contribute to architecture decisions, and mentor team members.

Develop and maintain Power BI dashboards and reporting solutions, write and optimize SQL queries, build data models and DAX calculations, validate data quality, and translate business requirements into actionable insights. The role involves stakeholder collaboration, troubleshooting reporting issues, documenting dashboard logic and data sources, and ensuring accurate, consistent reporting.

Design, build, and optimize scalable data pipelines and event-driven architectures on GCP. Develop Python applications, integrate external APIs, manage BigQuery and cloud storage solutions, and automate deployments with Cloud Build. Ensure pipeline performance, scalability, cost efficiency, data quality, governance, lineage, and security while collaborating with cross-functional teams and documenting technical solutions.

QA Analyst responsible for validating data warehouse and database deliverables through functional, regression, load, system, and UAT testing. Duties include writing test plans and SQL scripts, creating test data, tracking defects in Jira, validating fixes, investigating data-quality issues, and communicating test status to project teams and clients. The role requires SQL, ETL, data warehousing, cloud, Agile, and stakeholder communication experience.

Build and maintain cloud data pipelines, transformation workflows, orchestration, governance, and access controls for analytics products. Integrate APIs, Databricks, BI tools, and multi-tenant data platforms while troubleshooting quality and performance issues. Collaborate with product, engineering, DevOps, security, and client-facing teams on platform features, architecture documentation, infrastructure migrations, and production support.

Provides technical guidance throughout the software development lifecycle, including requirements analysis, design, development, testing, documentation, release processes, and feature delivery. Owns complex application features, improves code stability and reusability, identifies technical and security issues, integrates new technologies, estimates work, delivers training, shares knowledge, and mentors software engineers.

Leads quality assurance activities for data warehouse and database projects, including test planning, SQL scripting, functional and regression testing, defect tracking, data quality investigation, and UAT. Translates requirements into comprehensive test cases, validates fixes, communicates test status, establishes QA standards, and mentors 2–3 QA associates. Requires SQL, ETL, cloud, JIRA, Agile, and database testing expertise.

Maintains, cleans, manipulates, and secures operational and analytics data. Designs scalable data pipeline architectures, builds complex data sets and analytics tools, automates manual processes, improves infrastructure, troubleshoots database issues, and supports data, product, design, analytics, and data science teams with technical data needs.

Designs and develops scalable cloud data platforms and ETL/ELT pipelines using Python and SQL. Optimizes performance and costs, implements governance, security, quality, and compliance controls, and supports analytics consumption. Collaborates with architects and stakeholders, contributes to pre-sales prototypes and demos, mentors junior developers, conducts code reviews, and recommends improvements across AWS, Azure, and GCP environments.

Designs and implements multi-cloud data architecture solutions across AWS, Azure, and GCP. Responsibilities include data modeling, ETL/ELT pipelines, data warehousing, analytics platforms, governance, security, compliance, cost modeling, architecture proposals, and client presentations. The architect must remain hands-on with Python, SaaS data tools, MDM platforms, and agentic AI; support pre-sales and RFP responses; mentor junior architects; and integrate AI/ML into data architectures.

Leads quality assurance for software releases, including data warehouse and database testing, SQL and ETL validation, functional, regression, load, system, and UAT testing. Defines test strategies, writes test plans and cases, develops SQL scripts, manages defects, investigates data quality issues, validates fixes, communicates test status, establishes QA standards, and mentors 2–3 QA associates.

Designs and leads Salesforce Data Cloud solutions, including data models, ingestion pipelines, identity resolution, integrations, activation, segmentation, and personalization. Translates business requirements into technical designs, leads development teams, troubleshoots complex platform issues, and ensures data quality, privacy, governance, and performance. Collaborates with architects and stakeholders on strategy, roadmap planning, delivery, mentoring, and reusable technical standards.

Lead architecture and delivery of Salesforce Data Cloud solutions: design data models and ingestion pipelines, integrate with Marketing Cloud and MarTech, ensure identity resolution, privacy compliance, and performance, mentor engineers, and support audience segmentation and journey orchestration.

Lead technical design and implementation of Salesforce Marketing Cloud and Data Cloud, oversee integrations and performance tuning, define personalization strategies, guide cross-functional teams, configure and test solutions, and optimize campaign performance to deliver scalable, compliant CRM and marketing automation solutions.

Lead technical architect responsible for creating solution architectures, mentoring engineering leads, driving technical vision and roadmaps, ensuring scalable cloud-native platform services, enforcing CI/CD and code quality practices, and collaborating with Product, Security, DevOps and Architecture to deliver microservice-based web applications.

Lead architecture and delivery of Salesforce Data Cloud CDP solutions: design data models and ingestion pipelines, integrate Data Cloud with MarTech (MCP) for activation and personalization, ensure data quality/privacy compliance, troubleshoot integrations, mentor engineers, and support audience segmentation and journey orchestration.

Lead and scale multi-disciplinary software engineering teams delivering Promotions and Loyalty Services platforms. Own delivery quality, architecture, timelines, KPIs, risk mitigation, and client/stakeholder relationships. Provide technical guidance, support solutioning and pre-sales, manage hiring, performance, and career development, and drive engineering best practices across global teams.

Lead design and delivery of enterprise integration and AI-powered automation workflows. Build API-led, event-driven integrations, data transformation pipelines, microservices, and scalable low-code workflows (n8n, Azure Logic Apps). Mentor integration developers, enforce secure design and governance, integrate Azure OpenAI and other AI models, and collaborate across architecture, DevOps, QA, and business teams to ensure resilient, governed integrations.

Implement and administer Salesforce Data Cloud, including identity resolution, unified profiles, calculated insights, audience segmentation, and activation. Integrate CRM, marketing, web, mobile, commerce, and loyalty data using SQL, APIs, and ETL. Build predictive audiences and personalization use cases while supporting data governance, validation, troubleshooting, customer journeys, and omnichannel activation.

Lead business transformation strategy for global clients, advising C-suite stakeholders, leading pitches, developing transformation frameworks, and shaping digital media products. Translate market data and technical insights into persuasive strategic narratives, build reusable intellectual property, facilitate diagnostic sessions, and support cross-border growth. Collaborate with product, engineering, UX, and account teams on discovery, user journeys, prototyping, and product-led transformation. Measure commercial impact through attribution, media mix modeling, and transformation performance analysis.