Company description Publicis Production harnesses the power of Publicis Groupe's entire global production capabilities. Through our family of production brands, we access best-in-class production talent, models and technology worldwide. Our purpose is to deliver seamless, relevant and impactful consumer experiences across every touchpoint in every market. We do this with pioneering production solutions that drive performance in a data-led marketing landscape and help brands to win in the platform world. Overview We are seeking a proactive and self-motivated Senior Data Engineer with a proven track record in building scalable cloud-based data solutions across multiple cloud platforms to support our work in architecting, building and maintaining the data infrastructure. The specific focus for this role will start with GCP however we require experience with Snowflake and Databricks also. As a senior member within the data engineering space, you will play a pivotal role in designing scalable data pipelines, optimizing data workflows, and ensuring data availability and quality for production technology. The ideal candidate brings deep technical expertise in AWS, GCP and/or Databricks alongside essential hands-on experience building pipelines in Python, analysing data requirements with SQL, and modern data engineering practices. Your ability to work across business and technology functions, drive strategic initiatives, and independently problem solve will be key to success in this role. Responsibilities

Architect and maintain robust data pipelines (batch and streaming) integrating internal and external data sources (APIs, structured streaming, message queues etc.) Collaborate with data analysts, scientists, and software engineers to understand data needs and develop solutions Understand requirements from operations and product to ensure data and reporting needs are met Implement data quality checks, data governance practices, and monitoring systems to ensure reliable and trustworthy data Optimize performance of ETL/ELT workflows and improve infrastructure scalability

Qualifications Experience

Relevant experience in data engineering and solution delivery, with a strong track record of technical leadership Deep understanding of data modeling, data warehousing concepts, and distributed systems Excellent problem-solving skills and ability to progress with design, build and validate output data independently Deep proficiency in Python (including PySpark), SQL, and cloud-based data engineering tools Expertise in multiple cloud platforms (AWS, GCP, or Azure) and managing cloud-based data infrastructure Strong background in database technologies (SQL Server, Redshift, PostgreSQL, Oracle)

Desirable Skills

Familiarity with machine learning pipelines and MLOps practices Additional experience with Databricks and specific AWS such as Glue, S3, Lambda Proficient in Git, CI/CD pipelines, and DevOps tools (e.g., Azure DevOps) Hands-on experience with web scraping, REST API integrations, and streaming data pipelines Knowledge of JavaScript and front-end frameworks (e.g., React)

Additional information Diversity and inclusion is a core part of who we are at Prodigious London. We're committed to building an inclusive culture that encourages, celebrates and supports our wonderfully diverse employee group - whatever their age, gender identity, race, sexual orientation, physical or mental ability or ethnicity. Diversity and inclusion doesn\'t just fuel our creativity and innovation, it brings us closer to our people and audiences. We will continue to strive to create a culture and environment where everyone feels empowered and more importantly comfortable enough to bring their full, authentic selves to work. We are committed to providing reasonable adjustments for employees with disabilities and for candidates in our application process. If you need assistance or adjustment due to a disability, please contact us. #J-18808-Ljbffr