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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, Performance Marketing - **Company:** Publicis Groupe - **Location:** Agoura Hills, CA, United States - **Experience:** Experienced - **Salary:** $88,540.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Cloud Database, Cloud Storage, Software Quality, Databases, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Systems, Distributed Computing Environment, Python (Programming Language), Software Deployment, SQL Databases, Systems Integration, Google Cloud, File Transfer Protocol (FTP), Cloud Platform System, Data Ingestion, GitHub Copilot, Snowflake, Apache Spark, Data Lakes, Pyspark, Integration Frameworks, Operational Systems, Data Management, Data Lakehouse, Software Version Control, Data Pipelines, Database Tools and Utilities, Databricks - **Published:** July 31, 2026 - **Apply:** https://www.juju.com/job/00000000gknw2t ## About the Role Must have AdTech / MarTech industry experience, specifically in e-commerce, travel, and finance., What we look for: + 3-5 years of experience in Data Engineering, Analytics Engineering, or related disciplines. + Experience with cloud-based data platforms such as Databricks, AWS, Snowflake, or Google Cloud. + Familiarity with integrating AI and automation tools (e.g., GitHub Copilot, Natural Language Query tools) to enable you to move faster and deliver higher quality code. + Strong proficiency in SQL and Python. + Experience with Spark and distributed data processing (PySpark preferred). + Strong experience with data pipelines (ETL/ELT, event-driven, or workflow-based systems) + Understanding of Data Lake, Lakehouse, and Medallion architecture concepts. ## Description We are seeking a Data Engineer to design, build, and maintain scalable data platforms, pipelines, and infrastructure that support analytics, AI/ML, reporting, operational systems, and enterprise data products across the organization. This role will work across cloud platforms, data ingestion frameworks, and modern lakehouse architectures to deliver reliable, secure, and governed data solutions that enable business, product, engineering, and data teams. Responsibilities What you will be doing: + Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, SQL, and Spark-based technologies. + Serve as an advocate for AI-native engineering workflows, demonstrating how tools such as Claude Code, Codex, GitHub Copilot, Databricks Genie and related assistants can improve developer productivity, code quality, and operational efficiency. + Build and support data ingestion frameworks leveraging APIs, SFTP, cloud storage, databases, and third-party integrations. + Develop and maintain data products within a modern Data Lakehouse architecture, following Medallion (Raw, Bronze, Silver, Gold) design principles. + Create and optimize data workflows, orchestration processes, and monitoring solutions to ensure pipeline reliability, performance, and scalability. + Manage cloud-based data infrastructure and storage solutions across platforms such as Databricks, AWS, Snowflake, and Google Cloud. + Build operational tooling and monitoring dashboards to track pipeline health, resource utilization, uptime, and system performance. + Collaborate with Data Science, Analytics, Product, and Engineering teams to deliver trusted and scalable data assets. + Maintain source control, CI/CD processes, repository standards, and deployment best practices across data platforms. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [ Dev Digest 213: Petrol Prices, Agentic Workflows, AI Skills and CODE100!](https://www.wearedevelopers.com/magazine/718-dev-digest-213-petrol-prices-agentic-workflows-ai-skills-and-code100)