Senior Data Platform Engineer - Data Lake Platform

The Data Platform team ensures that all data generated at MOIA can be accessed and processed in our data platform. You will work at the core of MOIA's data engine room and interact with colleagues from 10+ different teams, providing automation, tools, and operating services so that data is processed in an efficient, secure and privacy compliant way.

What you'll do

• Enable teams across the company to get value from data using our internal tools and platform, working with engineers, analysts, and stakeholders across different tech stacks and business domains.
• 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 you'll need

• 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 have

• Exposure to data governance, GDPR and data privacy engineering.
• Experience with SQL in both analytical and transactional databases.
• Familiarity with orchestration frameworks for data pipelines, such as Apache Airflow.
• Experience designing and building (data) APIs.

What they offer

• Competitive salary (including bonus)
• Hybrid work setup with flexibility to work from home or offices
• Flexible working hours and work arrangements
• Home office budget and monthly expense allowance
• 30 vacation days, sabbatical and unpaid leave option
• Learning environment with continuous learning days, trainings, conferences, and coaching