Data Engineer- Specialist- Automotive

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Company description About Publicis Sapient Most companies in the AI era do one of two things: they advise, or they sell you a tool. We do both. Publicis Sapient is a technology company that provides enterprise AI platforms and services, which means we build our own AI platforms and bring the strategists, product thinkers, designers and engineers who make them work inside the world's most complex businesses. It's where people and products shape the future of enterprise, and where your ideas actually reach the organizations that run the world. If you want to question how things are done, learn continuously and do the best work of your career alongside 20,000 people across 28 countries, you're in the right place. Come build with us. Our Commitment to Inclusive Hiring We are committed to fostering and encouraging an inclusive and welcoming environment for everyone and we believe great talent comes from many different backgrounds, experiences, and perspectives. That's why we're committed to creating a hiring process where everyone has an equal opportunity to succeed and feel safe. We welcome applications from all backgrounds and identities including: race, ethnicity, nationality, gender, disability, sexual orientation, gender identity, or religion and value the diverse experiences, perspectives, and strengths they bring to our teams. If there's anything we can do to make our recruitment process more accessible or comfortable for you, please let us know. We're happy to provide reasonable adjustments throughout the application and interview process. You can contact us anytime at emeahiringteam@publicissapient.com. Your Safety Matters To Us At Publicis Sapient, we're committed to protecting candidates throughout every step of their journey with us. To help you stay safe from recruitment scams, please remember that our recruiters will only ever contact you from a Publicis Sapient email address. In some cases, we may partner with trusted, vetted recruitment agencies who will clearly identify themselves as working on behalf of Publicis Sapient. If you receive communication from any other domain claiming to represent us, please treat it with caution and contact us at emeahiring@pubicissapient.com Overview Why This Role Matters Publicis Sapient is looking for a Data Engineer Specialist who combines deep technical expertise with a genuine passion for people, leadership, and building exceptional products. In this hands-on leadership role, you'll have the opportunity to lead and grow a team of data engineers while staying close to the technology. You'll influence architecture, engineering standards, and delivery practices, and help build reliable, scalable data products that solve meaningful challenges. You'll thrive in this role if you enjoy turning complex data problems into elegant solutions, taking ownership from idea to production, and helping other engineers do their best work. You'll work with a modern cloud data stack-including GCP, Python, advanced SQL, Kafka, Cloud Composer, Terraform, and CI/CD-with the space to make technical decisions and continuously improve how the team builds and delivers. This role is an excellent opportunity for someone who would like to join an international global organization with a 'start-up' mentality. We highly value Openness, Collaboration, Learning Mindset and partner with our clients to drive positive outcomes. Where You'll Make an Impact Lead, mentor, and empower a team of data engineers, providing technical direction, guiding architecture decisions, and creating an environment where people can grow and do their best work. Take ownership of scalable data solutions from design and implementation through deployment, monitoring, optimization, and production support. Design, build, and optimize robust ETL/ELT pipelines across staging, warehouse, and data mart layers. Use advanced SQL to create high-performing transformations and define effective partitioning and clustering strategies. Shape warehouse architecture and schema design, including dimensional modelling and slowly changing dimension (SCD) patterns. Build Python connectors, orchestration scripts, reusable services, and data contract validation logic. Develop reliable event-driven and streaming solutions with Apache Kafka, with a strong focus on version-controlled, testable transformations and built-in assertions. Embed automated data quality and contract testing into the engineering lifecycle so issues are identified early and releases remain dependable. Build secure, scalable, and cost-efficient solutions on Google Cloud Platform (GCP), continuously balancing performance, reliability, and cloud spend. Use Cloud Composer / Apache Airflow to orchestrate workflows, schedules, and dependencies across the data ecosystem. Automate cloud infrastructure with Terraform or similar Infrastructure as Code (IaC) tooling, covering areas such as storage, datasets, IAM, and networking. Strengthen engineering practices through Git-based CI/CD, code reviews, automated testing, and controlled deployments using tools such as Cloud Build or GitHub Actions. Help shape standards for code quality, testing, documentation, observability, security, reliability, and data governance. Collaborate with architects, product teams, analysts, data scientists, and engineers to turn complex requirements into maintainable data products with tangible impact. What You'll Bring to the Team Significant hands-on experience in Data Engineering, designing and delivering production-grade data platforms and pipelines. Experience leading, mentoring, or technically guiding engineers while remaining actively involved in architecture and development. Strong SQL expertise, including complex transformations, query optimization, partitioning, and clustering across staging, warehouse, and data mart layers. Solid knowledge of data warehousing, dimensional modelling, schema design, and slowly changing dimensions (SCD). Strong hands-on Python skills for connector development, data processing, automation, orchestration, and validation frameworks. Practical experience building cloud-native data solutions on GCP, with an understanding of performance and cost optimization. Hands-on experience with Apache Kafka and event-driven or streaming architectures. Experience building automated data quality, contract-validation, and transformation tests as part of version-controlled engineering workflows. Additional information What You'll Get in Return A fast-paced tech environment Continuous growth & learning Open feedback culture Room for own initiative & ideas Transparency about results & strategy Recognition & reward for hard work Working with a flexible schedule Medical subscription Meal tickets Extra vacation days - starting with 25 vacation days Many others perks