Additional Information
Our world is transforming, and PTC is leading the way. Our software brings the physical and digital worlds together, enabling companies to improve operations, create better products, and empower people in all aspects of their business.
Our people make all the difference in our success. Today, we are a global team of nearly 7,000 and our main objective is to create opportunities for our team members to explore, learn, and grow - all while seeing their ideas come to life and celebrating the differences that make us who we are and the work we do possible.
As a Data DevOps Engineer , you will design, build, and operate the core platforms, tooling, and automation that power our data engineering ecosystem across Central Data Operations (CDOPS). Your mission is to ensure data engineers can move fast without sacrificing reliability, security, or observability .
You will own the runtime platforms (especially Apache Airflow and Power BI/Microsoft Fabric), container images , CI/CD pipelines , and developer workflows that support data ingestion, transformation, and analytics.
This role sits at the intersection of data engineering and DevOps , with a strong focus on production excellence, operational rigor, and developer experience (DX) .
Your work will directly enable BI, AI, and Analytics teams by providing stable, well‑instrumented, and easy‑to‑use data platforms.
This is an opportunity to shape Data DevOps practices from the ground up and lead technical direction with a high ownership and platform impact role.
Day‑to‑Day Responsibilities
Airflow Platform Architecture & Engineering
Design, build, maintain, and evolve Apache Airflow platform used by the CDOPS data team.
Develop and version custom Airflow Docker images, including dependency management, plugins, and secure base images.
Improve orchestration scalability, resilience, and upgrade strategies.
CI/CD & Automation across Airflow, Microsoft Fabric/Power BI, and Snowflake Data warehouse
Design, implement, and operate CI/CD pipelines for: Airflow DAG validation, testing, and deployment
Container image build and release processes
Environment configuration promotion and release management
Build, maintain, and enhance the CDOPS Data Warehouse CI/CD framework using GitLab, Terraform, Snowflake, and DBT
Design and evolve CI/CD pipelines for Microsoft Fabric and Power BI deployments
Implement end-to-end orchestration and dependency management across platforms, ensuring reliable and scalable data workflows
Platform Reliability, Operations & DevEx
Architect and run containerized data systems using Docker and Docker Compose.
Debug and operate Linux‑based systems (CPU, memory, I/O, networking, DNS).
Improve developer experience through: Local development tooling
Platform templates and automation
Clear documentation and onboarding paths
Eliminate toil and manual operational work through automation.
Monitoring, Observability & Incident Management
Design and operate platform‑level observability using Prometheus and Grafana.
Define and maintain metrics, dashboards, and alerting standards for data platforms.
Lead incident response, root‑cause analysis, and post‑incident improvements.
Maintain runbooks, system diagrams, and operational documentation.
Collaboration & Cross‑Functional Support
Partner with Data Engineering, BI, and AI teams to design robust data flows and operational solutions.
Translate developers' needs into scalable platform solutions.
Provide technical leadership through code reviews, design reviews, and architectural discussions.
Mentor engineers in production‑grade data systems, DevOps practices, and operational excellence.
Preferred Skills & Knowledge
Python skills for automation and platform tooling.
Strong knowledge of Docker (DockerFile, Compose) and Linux systems.
Hands‑on experience with Apache Airflow architecture and operations.
Proven experience building and maintaining CI/CD pipelines.
Expertise in monitoring and observability tooling (Prometheus, Grafana).
Strong Git‑based development practices and familiarity with Infrastructure‑as‑Code concepts.
Exposure to Snowflake, DBT, Microsoft Fabric, Terraform, AIRBYTE, Apache Hop, Hashicorp Vault is a plus.
Clear communicator with strong system‑level thinking.
Preferred Experience
Running Airflow in production at scale (Celery or Kubernetes executors).
Designing monitoring architectures with Prometheus and grafana
Experience in SaaS environments.
Managing multi‑container applications, secure secrets handling, and production troubleshooting.
Willingness and motivation to progressively take on Data Engineering responsibilities as part of career growth.
Ptc · Rom-bucharest, Po