Quick overview
Job description
We are seeking a Senior Data DevOps Engineer to join our team as a strong individual contributor who designs and maintains data infrastructure, automates delivery processes, and improves pipeline reliability. This role focuses on working autonomously on complex problems and mentoring less experienced colleagues, without team management responsibilities.
Responsibilities Develop and maintain infrastructure for data pipelines Build and improve CI/CD for data processes and infrastructure Automate deployments through Infrastructure as Code Set up pipeline orchestration, monitoring, and alerting Diagnose and resolve incidents, improving stability and performance Participate in code review and mentor junior/middle engineers Collaborate with data engineers and analysts to optimize data workflows Requirements 3+ years of experience in DevOps or Data Engineering Background in supporting AI/ML workloads and building or maintaining ML infrastructure (MLOps) Hands-on experience with one cloud platform (AWS, Google Cloud Platform, or Azure) Proficiency in Docker, Kubernetes, and Terraform (or equivalent IaC) Expertise in pipeline orchestration tools such as Airflow, Dagster, or Prefect Familiarity with data lake/DWH concepts and big data processing (Spark, Kafka, or equivalent) Strong programming skills in Python, SQL, and Bash Competency in CI/CD setup with GitLab CI, GitHub Actions, or Jenkins Autonomy and ownership of outcomes Willingness to share knowledge and mentor Attention to detail, reliability, and quality English proficiency at an Upper-Intermediate level (B2) or higher Nice to have Knowledge of monitoring and observability tools (Prometheus, Grafana, ELK) Exposure to LLM/GenAI tooling Understanding of data security and data quality practices
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