Jobs at dentsu

Lead QA to embed quality across solution delivery: define and maintain unit tests, design telemetry pipelines, manage defects and test environments, mentor engineers, present risks to stakeholders, and lead QA for data migration and performance testing of Azure-hosted, containerized distributed systems.

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 design and implementation of scalable ETL/ELT data platforms on GCP. Develop high-performance SQL models and Python data applications, architect real-time event-driven solutions, ensure governance, security, CI/CD, and mentor engineering teams while collaborating with stakeholders to deliver reliable, cost-efficient data solutions.

Design and implement scalable, secure multi-cloud data architectures; support pre-sales with technical presentations, demos, and RFP/RFI responses; produce solution proposals, architecture diagrams, and cost estimates; mentor junior architects and collaborate with stakeholders to translate requirements into analytics-ready solutions.

Build and maintain scalable Azure and Databricks ETL/ELT pipelines using SQL and Python/PySpark. Design cloud-native data lakes, ingest/process data with ADF/ADLS, optimize data models, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business teams.

Lead design and development of scalable cloud data platforms and ETL/ELT pipelines across AWS/Azure/GCP. Build and optimize data warehouses/lakehouses, implement MDM and governance, support analytics/BI, mentor junior engineers, and contribute to presales PoCs and solution designs.

Design and maintain scalable data architectures and ETL/ELT pipelines; write optimized SQL and Python code; deploy solutions on AWS (S3, Lambda) and Snowflake; implement data quality checks and monitoring; support GenAI initiatives; collaborate with stakeholders; document work and perform mid-to-complex tasks with minimal supervision.

Design, implement, and govern end-to-end Adobe Journey Optimizer journeys and AEP data models. Build audience segments, API integrations, channel configurations, decisioning logic, ensure data governance and privacy compliance, support QA/UAT and optimize journey performance.

The Tech Lead will oversee integration and automation solutions, create technical specifications, guide the tech team, ensure timely delivery, and support impact analysis on systems.

The role involves implementing and optimizing Adobe marketing solutions, providing expertise in campaign management, data modeling, and technology integration while collaborating across teams.

This role leads AEM technical excellence and innovation, providing architectural oversight and fostering high-performance teams while driving AI integration and best practices.