Senior DataOps Engineer | B2B Cooperation | Poland

23k - 27k PLN23 000 - 27 000 PLN/ mies./ mies.B2BB2B (netto)

SeniorZdalnie·WarszawaInne·B2B

#472839·Dodano 2 dni temu·4

Źródło: justjoin.it

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Tech Stack / Keywords

Databricks GCP BigQuery Terraform DockerPower BILangFusePython SQLAirbyte

Podsumowanie oferty

As a DataOps Engineer in the Data Team, you will keep the cloud data platform reliable, secure and cost-effective. You will manage infrastructure, deployments, monitoring and costs across GCP and Databricks, supporting reporting, internal data systems and the AI analytics environment.

Wymagania

Hands-on experience with Terraform.
Hands-on experience with CI/CD pipelines, Docker and Bash.
Hands-on work in a cloud environment, preferably GCP, including IAM, networking and cost management.
Experience with monitoring, alerting and handling production incidents.
Experience operating orchestration tools such as Dagster or Airflow.
Working knowledge of Databricks, including jobs, clusters and workspace administration.
3+ years of commercial experience with Python and SQL.
Proficiency in deploying and running production-grade applications.
Very good communication skills and ability to work with technical and non-technical stakeholders.
Excellent team player who embraces teamwork and mutual support.
Fluency in Polish (C1+) and strong command of English (B2+).

Nice to have:

Previous experience in a DevOps, SRE, Platform Engineering or Data Engineering role.
Experience with Databricks Asset Bundles and Unity Catalog.
Experience with Airbyte, DataHub or ClickHouse.
Experience running AI/LLM applications in production, for example with Langfuse.
Commercial experience with Spark.

Obowiązki

Maintain and automate the cloud data platform (GCP, Databricks) that powers the reporting suite and internal data systems.
Manage infrastructure as code with Terraform for GCP and Databricks.
Build and maintain CI/CD pipelines in GitLab, including Databricks deployments with Asset Bundles.
Maintain Docker images and runtime environments for Dagster and Airbyte, with zero-downtime upgrades.
Own development and production environments and the release process.
Set up platform and pipeline observability, including alerting, metrics, logs and data freshness monitoring.
Define SLOs for key pipelines, handle incidents, write runbooks and run postmortems.
Manage access, IAM, service principals and secrets, following the principle of least privilege.
Monitor and optimize cloud costs across GCP and Databricks.
Maintain and support development of Hermes, the AI analytics environment, including deployments, BigQuery datasets, monitoring and tracing in Langfuse.
Support data lineage, cataloguing and governance with DataHub.
Work with Data Engineers to run pipelines reliably in production, and with analysts on data availability, SLAs and self-service access.
Automate repetitive operational work and help retire legacy tools.

Benefity

Flexible project collaboration setup.
Planned service breaks aligned with contract terms.
Opportunity to access selected knowledge-sharing initiatives.

Inne informacje

Recruitment process: an introductory call with the Recruiter (up to 45 minutes), a technical interview with the Hiring Manager and Data Engineer (up to 60 minutes), and a team fit interview with the Hiring Manager and Data Analyst (up to 60 minutes).

Profitroom

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