Own and lead the big data infrastructure platform, including deploying, upgrading, and operating HDFS, object storage, Iceberg, monitoring, and alerting. Drive infrastructure modernization, migrate Iceberg catalogs, implement multi-tenant quotas, improve observability, and support large-scale data architecture changes. Collaborate with a parallel infrastructure engineer, share solutions, provide coverage, and influence platform architecture.
As a Big Data Infrastructure Engineer in the Big Data Platform team, you’ll own the big data infrastructure of our international contour and be its technical lead. You’ll deploy, upgrade and operate the core services of the platform: HDFS, S3-compatible object storage (Apache Ozone), Iceberg and others. You’ll start by helping run an infrastructure pilot that changes how the platform is used: a small number of very large datasets will become thousands of small tables. You’ll introduce compute and storage quotas for business units, migrate us from the default Iceberg catalog to a more capable one (Lakekeeper or Gravitino), and rebuild monitoring and alerting so alerts mean something again. You’ll work closely with an engineer who runs the same stack in a parallel contour. You’ll share approaches and solutions with them and cover for each other. Our infrastructure runs on the latest versions of everything, and we actively replace outdated tools. The role suits an experienced engineer who wants real ownership and a big say in architecture.
Requirements
- 5+ years of experience designing, deploying and operating big data platforms.
- Hands-on experience with HDFS / Hadoop: deployment, version upgrades, troubleshooting.
- Hands-on experience deploying and operating S3-compatible object storage. Apache Ozone is ideal, but MinIO or similar solutions also count.
- Experience with Apache Iceberg.
- Experience setting up monitoring and alerting for data infrastructure.
- English B2.
- Ability to work in the GMT+3 time zone (up to 3 hours difference).
Nice to have
- Experience with Trino, Kafka or Flink.
- Experience with Iceberg REST catalogs (Lakekeeper, Gravitino, Polaris or similar).
- Experience setting up resource quotas and cost allocation in a multi-tenant data platform.
- Hands-on use of AI tools, such as Copilot or agents, to speed up your work.
Benefits
- Flexible schedules and opportunity to work remotely.
- Ambitious and supportive team who love what they do, appreciate each other, and grow together.
- A structured onboarding, a personal development plan, and regular internal lectures and demos from the team.
- Internal programs for adaptation and training, development of soft skills, and leadership abilities.
- Partial compensation for participating in external training and conferences.
- Corporate English school: Group and individual lessons, speaking clubs with colleagues from all over the world.
- Corporate prices on hotels and travel services.
- MyTime Day Off - an extra non-working day without loss of compensation.
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