We are looking for a Staff Data Engineer to lead the design, development, and operation of our cloud-native data platform on AWS. This role goes beyond traditional data engineering and sits at the intersection of data and platform engineering. You will drive the architecture

and deployment of scalable data services, APIs, and pipelines, while shaping our Kubernetes-based infrastructure and engineering standards.

Your responsibilities:

Architect and operate scalable data platforms using AWS services (e.g., S3, Glue, Lambda, EMR)
Design, build, and maintain batch and real-time data pipelines
Develop and deploy containerized data services and APIs on Kubernetes (EKS), including CI/CD integration
Own infrastructure as code (e.g., Terraform, CloudFormation) for data and platform components
Manage and optimize Kubernetes workloads (resource management, autoscaling, observability, networking)
Build and maintain internal data APIs and microservices for data access and processing
Ensure high standards for data quality, reliability, security, and governance
Collaborate with systems engineers, ML engineers and analytics teams to deliver end-to-end data solutions
Lead technical decision-making, set best practices, and mentor engineers across teams

Job requirements

Your profile

Extensive experience in data engineering and backend/platform engineering
Strong expertise in Python, Java, SQL, and AWS ecosystem
Hands-on experience with Kubernetes (EKS), containerization (Docker), distributed event streaming frameworks (Kafka), and microservices architecture
Experience deploying and managing APIs and services in Kubernetes environments
Solid understanding of CI/CD pipelines and infrastructure as code
Familiarity with orchestration tools (e.g., Airflow)
Strong system design skills and ability to operate at scale
Excellent communication and leadership skills

As a Staff Data Engineer, you will play a key role in bridging data engineering with modern platform engineering practices, ensuring our AWS-based data ecosystem is scalable, reliable, and developer-friendly.

Data Engineer (m/f/x)