Programmatic Tech Lead

Director of Technology at Publicis Groupe

We are seeking a passionate and experienced Director of Technology to join our Data Foundation Platform team, working closely to architect and implement scalable data ingestion, processing, and storage solutions for a marketing channel (Search, Social, Programmatic, or Commerce). This role powers One Suite's AI-driven insights and enables AI-native data platform design within Publicis Groupe Performance solutions.

The Performics function strategizes and provides digital activation services for global advertisers across 57+ markets. This role offers a clear growth path into AI Orchestration or Agent Studio leadership as the platform evolves.

• Lead data architecture design and implementation for the assigned marketing channel (Search, Social, Programmatic, or Commerce), ensuring scalable and AI-optimized data flows.
• Own the technical roadmap for data foundation platform components, aligning with the One Suite product strategy and AI orchestration requirements.
• Design and implement robust data ingestion pipelines from marketing APIs, third-party sources, and campaign management platforms, with data formats optimized for AI/LLM consumption.
• Architect scalable data processing workflows for real-time streaming and batch analytics, including:
• Campaign performance data aggregation and transformation
• Customer journey data processing and enrichment
• Marketing attribution and conversion tracking
• AI training dataset preparation and feature engineering
• Build enterprise-grade data storage solutions optimized for traditional analytics and AI/ML model training and inference.
• Establish comprehensive data quality frameworks with automated monitoring, validation, lineage tracking, and alerting systems.
• Drive AI-native data platform design, integrating vector-ready processing for embedding generation, similarity search, and RAG system optimization.
• Collaborate closely with cross-functional teams on cross-channel data platform strategy, architecture standards, and integration patterns across Search, Social, Programmatic, and Commerce channels.
• Provide technical guidance and mentorship to junior data engineers, fostering best practices in data engineering and AI integration.
• Lead cross-functional collaboration with AI Orchestration, Agent Studio, and frontend teams to ensure seamless data integration and optimal performance.
• Implement data security, privacy, and compliance frameworks for enterprise marketing data handling across global markets.
• Research and evaluate emerging AI-enhanced data processing tools, vector databases, and data platform technologies for continuous platform improvement.
• Design and implement high-performance data APIs that serve both traditional analytics dashboards and AI agent workflows with sub-100ms response times.
• Establish comprehensive monitoring and observability for data pipelines, ensuring 99.9% uptime and proactive issue detection.

• Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
• 5+ years experience in data engineering with emphasis on high-volume marketing data processing and real-time analytics.
• 2+ years experience in technical leadership roles, including mentoring team members and driving architectural decisions.
• Production experience building and maintaining data pipelines processing millions of marketing events daily.
• Strong expertise in data ingestion from marketing platforms (Google Ads, Facebook Ads, programmatic DSPs, Amazon Advertising).
• Advanced knowledge of data processing frameworks including Apache Spark, Kafka, Airflow, and modern streaming technologies.
• Expert-level proficiency in Python and SQL, with hands-on experience in at least one additional language (Scala, Java, or Go).
• 1+ years demonstrable experience working with AI/ML systems, including understanding of data requirements for LLMs, RAG architectures, and vector processing.
• Deep understanding of cloud data infrastructure (AWS, GCP) including data lakes, warehouses, and real-time processing services.
• Strong experience with both SQL and No
  
  SQL databases (PostgreSQL, MongoDB, Redis, Elasticsearch) and data modeling for analytics.
• Familiarity with AI data patterns including embedding generation, vector similarity search, and data preparation for model training.
• Experience with containerization technologies like Docker and Kubernetes for data service deployment.
• Strong advocate for data quality, testing methodologies, and CI/CD pipelines for data platform development.
• Solid understanding of data structures, algorithms, and distributed systems design principles.
• Excellent communication and collaboration skills, with ability to work effectively with both technical and business stakeholders.

• Compensation Range: $132,715 - $208,840 annually (pay determined based on skills, qualifications, and experience).
• Medical, dental, vision, disability, 401(k), parental and family care leave, tuition reimbursement, and flexible time…