Senior Data Platform Engineer (all genders) - Data Lake Platform

Job description

Join us as a Senior Data Platform Engineer (all genders) in our Data Lake Platform team and help shape the future of autonomous mobility! The Data Platform team ensures that all data generated at MOIA can be accessed and processed in our data platform. We rely on a wide variety of AWS services to build our data products and keep our stack as serverless as possible. You will work at the core of MOIAs data engine room and interact with colleagues fr om 10 + different Teams. We provide automation, tools, operate services and evangelize best practices so that data at MOIA is processed in an efficient, secure and privacy compliant way. We strive towards enabling our users to work as independently and self-sufficiently as possible. What you will do Enable teams across the company to get value from data using our internal tools and platform . You'll work with engineers, analysts, and stakeholders across. You'll work with engineers, analysts, and stakeholders across different tech stacks and business domains - for a platform team. Communicating well is as important as the code we write. Set up and govern Amazon SageMaker Unified Studio (SMUS) for other teams, so they can work independently without us becoming a bottleneck. Keep our AWS data infrastructure available, scalable, and secure, and own the operational side of what you build. Build and optimize event-driven ingestion pipelines with Amazon Kinesis, Amazon Data Firehose and AWS Lambda. Help the team grow. What will help you to fulfill your role You want to work as a team, not just alone : pair programming, sharing knowledge, mentoring and clear communication should feel natural in your day-to-day work rather than overhead. Strong programming skills in Python. Experience with the JavaScript/TypeScript ecosystem and/or a JVM language is a plus. Experience developing and running applications in cloud-native environments (for example AWS Lambda and S3), deployed through Infrastructure as Code with CDK or Terraform. A solid DevOps foundation: CI/CD, containers, monitoring and alerting. Working knowledge of table and data formats such as Apache Iceberg, Parquet, Protocol Buffers. Hands-on experience applying AI in a data context: to speed up your own development, to automate routine work, and to help others do the same. Nice-to-Haves: Exposure to data governance, GDPR and data privacy engineering. Experience with…