Mid/Senior DevOps

Opis oferty

We’re looking for a DevOps Engineer to join a project building a cloud-native data lakehouse platform for a global financial services company.

The platform is built on AWS, Kubernetes, Apache Flink, Spark, Airflow, JupyterHub, and Apache Iceberg. The current phase focuses on deploying and adapting the solution to the client’s AWS environment, integrating with their IaC standards, CI/CD pipelines, identity management, networking, and security controls.

The goal is to deliver an MVP capable of processing high-volume Kafka event streams, supporting tenant workloads, enabling data analysis, and providing full monitoring and alerting.

Working hours: Core working hours align with the Polish time zone. Due to collaboration with global teams, including the US, occasional planned meetings may take place between 17:00–21:00 CET/CEST. Flexibility to join key project and stakeholder meetings is expected.

⚠️ Successful completion of the client's background screening process is required before joining the project. This may include identity, employment history, and criminal record verification.

Wymagania

4+ years of experience in DevOps/Platform Engineering, including hands-on experience.

Knowledge of Kubernetes and AWS (EKS, networking, IAM/IRSA, S3, KMS) in production environments.

Practice with Terraform and/or AWS CDK, Helm, and CI/CD (Jenkins preferred), as well as cloud security and observability.

Experience with data-intensive platforms, including technologies such as Kafka/Spark/Flink, Airflow/ Iceberg.

Confidence in direct client communication.

Zakres obowiązków

• Supporting the deployment of the platform into the client's AWS non-production environment and collaborating with the client's infrastructure, security, and identity teams.
• Building and maintaining Jenkins pipelines for builds, image publishing, and deployments, including dependency ordering, bootstrap, and database migration steps.
• Being co-responsible for integrating platform services such as Polaris, Airflow, JupyterHub, and Grafana with the client's corporate OIDC identity provider and configuring directory group-to-role mappings.
• Co-configuring networking, TLS certificates, workload identities (IRSA), secrets management, and KMS encryption.
• Supporting and optimising Flink, Spark, and Airflow workloads running on Kubernetes, including data ingestion from Kafka into Iceberg.
• Configuring and maintaining observability tools, including Prometheus, Thanos, Grafana dashboards, Loki, and Alertmanager.
• Preparing technical documentation, deployment instructions, and validation evidence, and providing progress updates to client stakeholders.
• Collaborating with the team on technical planning, code reviews, and knowledge sharing.