DataOps Engineer

About the role

The DataOps Engineer will work closely with data and engineering teams to build automated solutions for infrastructure, platform management and continuous delivery of large‑scale data pipelines.

Key responsibilities

• Evaluate data importance and manage production of data pipelines.
• Configure monitoring tools for system performance, uptime and daily operations.
• Identify and implement automation opportunities to streamline operations.
• Design and develop scalable data engineering assets and frameworks.
• Expand platform capabilities by integrating new data sources.
• Implement internal process improvements, including automation and infrastructure redesign.
• Define and build data pipelines that enable faster, data‑informed decision‑making.
• Migrate solutions from legacy systems to cloud data platforms.
• Maintain platform tasks such as user management, audit, resource utilisation and alerts.
• Modify existing ETL processes for automation and accommodate data structure changes.

Required profile

• Minimum 2 years of experience in a similar DataOps or data engineering role.
• Bachelor's degree in Information Science, Information Technology, Computer Science, Physics or a related field.

Required skills

• Relational databases and data platforms
• Kubernetes
• Azure or AWS (IaaS)
• Airflow and Mlflow
• Hadoop, Hive and big‑data ecosystem
• Kafka, NiFi and ETL tools
• Python
• Feast API
• Git and CI systems (e.g., Jenkins)
• Windows, UNIX/Linux operating systems
• IP networking fundamentals (TCP/IP, HTTP, DNS)
• Security fundamentals