Data Engineer- Specialist- Automotive

Tremend is the newest global software engineering hub for Publicis Sapient. For over 20 years, the company has been infusing its advanced technical expertise into complex and innovative solutions that meet today's digital transformation needs and pave the way for a better and smarter future. By joining forces with Publicis Sapient we're accelerating the impact, providing a good mix of talented engineers, technology, continuous improvement, innovation, and R&D. Here, you'll have the opportunity to unleash your potential, powering up advanced software solutions for some of the world's most iconic brands. Embrace your passion for technology, creativity, and continuous improvement, and join us in making a difference through engineering.

We’re 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.

Responsibilities

• 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.

Skills & Experience

• 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.

Besides an exciting job in a tremendous team, here's what you can expect:

• 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