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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Manager, Data Engineering, DTAI - **Company:** Publicis Groupe - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $120,000.0 - $170,000.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Software as a Service, Cloud Computing, Code Review, Continuous Integration, Information Engineering, Data Infrastructure, Python (Programming Language), Operational Databases, Standard Sql, Software Construction, Software Engineering, Google Cloud, System Availability, Large Language Models, Backend, Containerization, Data Lakes, Information Technology, Virtual Agents, Api Design, Software Version Control, Data Pipelines, Docker, Databricks - **Published:** October 2, 2026 - **Apply:** https://www.careerjet.com/job/us6f46afd032ada1c7ec92693e7cab51c8/eaa ## About the Role * Bachelor's degree in Computer Science, Engineering, Data Science, or a related technical field * 5+ years of experience in data engineering, platform engineering, software engineering, or a related discipline * Strong proficiency in Python and SQL * Hands-on experience building solutions in Databricks or comparable modern data platforms * Experience designing and supporting production data pipelines and cloud-based applications * Experience building APIs and backend services * Familiarity with software engineering best practices including testing, source control, CI/CD, and code reviews * Strong problem-solving, communication, and collaboration skills * Comfortable working in fast-paced, evolving environments with a high degree of ownership Additional Qualifications (Nice to have): * Experience with Google Cloud Platform, AWS, or Azure * Experience with Databricks technologies such as Delta Lake, Unity Catalog, and Lakehouse architectures * Experience with containerization technologies such as Docker * Exposure to infrastructure-as-code and cloud deployment practices * Experience working with LLMs, AI-enabled applications, or intelligent automation workflows * Experience supporting marketing, media, advertising, or customer analytics data environments * Familiarity with adtech, martech, CRM, CDP, or business intelligence platforms ## Description The Manager, Data Engineering will help build the technical foundation that enables scalable analytics, automation, and AI-powered capabilities across Infinite Roar. This is a highly hands-on role focused on transforming analytical prototypes and business workflows into production-grade solutions that are secure, reliable, and scalable. Working closely with Analytics, Audience Strategy, and Platform Intelligence teams, you will design and deliver data products, APIs, and engineering capabilities that accelerate decision-making and unlock new opportunities across the organization. We're looking for a builder who enjoys taking ideas from concept to production and thrives at the intersection of data engineering, software development, and emerging AI technologies. What Success Looks Like: You enjoy solving complex business problems through technology and are passionate about building reusable solutions that help teams move faster and operate more efficiently. You bring strong data engineering fundamentals, modern software engineering practices, and a pragmatic mindset toward AI and automation. You know when advanced AI techniques create value and when a well-designed data pipeline, API, or application is the better solution. Most importantly, you're excited about helping shape the future technical foundation of a growing Platform Intelligence organization. Responsibilities Data Platform & Engineering * Design, build, and maintain scalable data pipelines, analytical solutions, and data products using Databricks, Python, and SQL * Develop and optimize workflows that support analytics, automation, reporting, and AI-driven applications * Establish and maintain best practices for data quality, governance, security, and performance * Transform analytical prototypes into production-ready services, applications, and reusable components * Continuously improve platform reliability, scalability, maintainability, and cost efficiency Software & Platform Development * Build and maintain APIs, backend services, and shared engineering capabilities that support internal teams and client-facing solutions * Implement modern software engineering practices including testing, code reviews, documentation, version control, and CI/CD * Partner with technology teams to deploy and support secure, scalable cloud-based solutions * Troubleshoot and resolve production issues while continuously improving operational performance and observability AI & Automation * Partner with analytics and strategy teams to identify opportunities where AI and automation can improve workflows and decision-making * Develop and support intelligent workflows that combine analytical models, APIs, and modern AI capabilities * Evaluate emerging AI technologies and help determine practical applications across internal and client-facing use cases * Contribute to the evolution of the organization's AI and Platform Intelligence capabilities Cross-Functional Leadership * Collaborate with analytics, audience strategy, and business stakeholders to translate requirements into scalable technical solutions * Communicate technical concepts and recommendations clearly to both technical and non-technical audiences * Contribute to engineering standards, knowledge sharing, mentoring, and technical best practices across the organization ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story)