Senior DataOps Engineer - B2B Cooperation

Profitroom; United States; Remote; USD 71,000 - 86,000; Full time

Benefits offered by this job

DevOps background

Databricks Asset Bundles

Airbyte/DataHub/ClickHouse

LLMOps with Langfuse

Spark experience

Job summary

Profitroom is seeking a skilled DataOps Engineer to own and automate our data platform, ensuring reliability, security, and cost efficiency. You will work closely with engineers and analysts to power reports, dashboards and AI tools through a robust data infrastructure.

You will manage CI/CD pipelines in GitLab, Databricks deployments, Docker runtimes for Dagster and Airbyte, and implement observability, SLOs, and cost optimization across GCP and Databricks.

Qualifications

• Terraform and IaC experience.
• CI/CD pipelines, Docker and Bash experience.
• Hands-on work with a cloud environment, preferably GCP.
• Experience with monitoring and production incidents.
• Experience operating orchestration tools (Dagster or Airflow).
• Working knowledge of Databricks (jobs, clusters, workspace administration).
• 3+ years of commercial experience with Python and SQL.
• Proficiency deploying and running production-grade applications.
• Excellent communication with both technical and non-technical stakeholders.
• Team player with strong collaboration skills.
• Fluency in Polish (C1+) and English (B2+) required.

Responsibilities

• Maintain and automate a cloud data platform (GCP, Databricks).
• Manage infrastructure as code with Terraform for GCP and Databricks.
• Build and maintain CI/CD pipelines in GitLab and Databricks deployments with Asset Bundles.
• Maintain Docker images and runtimes for Dagster and Airbyte with zero-downtime upgrades.
• Own development and production environments and the release process.
• Set up observability: alerting, metrics, logs and data freshness monitoring.
• Define SLOs for pipelines, handle incidents, write runbooks and postmortems.
• Manage IAM, service principals and secrets following least privilege.
• Monitor and optimize cloud costs across GCP and Databricks.
• Maintain Hermes AI analytics environment deployments and monitoring (Langfuse).
• Support data lineage, cataloguing and governance with DataHub.
• Collaborate with Data Engineers to run pipelines reliably and ensure data availability.

Skills

Terraform

GitLab CI/CD

Docker

Bash

GCP

Databricks

Observability

Dagster

Airflow

Python

SQL

Deployment

Communication

Teamwork

Polish

English

Tools

Databricks Asset Bundles

Unity Catalog

Airbyte

DataHub

Langfuse

Job description

Do you love automating things and keeping data platforms reliable? We are looking for a skilled DataOps Engineer to join our Data Team and make sure our data platform runs reliably, securely and cost-effectively, helping drive our company toward a more data-driven future.

The role

You will own the operational side of our data platform: infrastructure, deployments, monitoring and costs. Your work will have a direct impact on product development, customer support processes and overall business strategy, because every report, dashboard and AI tool we build depends on the platform you keep running. If you enjoy taking ownership, automating everything you can and working closely with engineers and analysts, this role is an excellent opportunity for you!

What you’ll actually do

• Maintain and automate our cloud data platform (GCP, Databricks), which powers our 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 observability for the platform and pipelines: 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 (FinOps) across GCP and Databricks.
• Maintain and support the development of Hermes, our AI analytics environment (deployments, BigQuery datasets, monitoring and tracing in Langfuse).
• Support data lineage, cataloguing and governance with DataHub.
• Work with Data Engineers to run their pipelines reliably in production, and with analysts on data availability, SLAs and self-service access.
• Automate repetitive operational work and help retire legacy tools.

Requirements

What we're looking for

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

Nice to have

• Background: Previous experience in a DevOps, SRE, Platform Engineering or Data Engineering role.
• Databricks tooling: Experience with Databricks Asset Bundles and Unity Catalog.
• Data tooling: Experience with Airbyte, DataHub or ClickHouse.
• LLMOps: Experience running AI/LLM applications in production (e.g. Langfuse).
• Spark: Commercial experience with Spark.

What comes with the job

Contract terms: B2B cooperation. Monthly compensation range: 25 000 - 30 000 PLN , depending on experience and the agreed scope of services.

• International technology and product projects
• Flexible project collaboration setup
• Planned service breaks aligned with contract terms
• Opportunity to collaborate with experienced product and technology teams
• Opportunity to access selected knowledge-sharing initiatives
• Intro call with the Recruiter (up to 45 minutes).
• Technical interview with Hiring Manager and Data Engineer (up to 60 minutes).
• Team fit interview with Hiring Manager and Data Analyst (up to 60 minutes).