DataOps Engineer

Job description

• The DataOps team is responsible for the seamless integration, release, and monitoring of mission-critical data pipelines and workflows.
• Currently based in Geneva, we are expanding our global presence by establishing a virtual DataOps team in Singapore.
• This role reports to the local IT manager for applications and plays a key role in our "follow-the-sun" support model to ensure continuous data engineering and observability, ETL, batch processing, and data management.
• Our data platform is evolving into a more converged stack that supports data streams, batch-based lakehouses, and a microservices-based data streaming integration model that facilitates the development of CI/CD processes.
• To support this work, Python, SQL, and CI/CD are essential skills. This role requires an experienced and enthusiastic developer who values these technologies and knows how to build, test, deploy, and monitor the operational components of a sophisticated data management and observability platform.

Main responsibilities

• Assume operational responsibility for specific data changes (change management, quality assurance, and other IT procedures).
• Monitor and ensure the business continuity of critical data pipelines across the entire group using our on-premises and cloud services.
• Design, implement, and optimize data pipelines in batch and streaming modes.
• Follow and apply CI/CD practices to automate and streamline deployments and integrations.
• Create, maintain, and improve documentation and operating procedures as part of operational standards.
• Collaborate with cross-functional teams to address governance issues and improve integration and data management.
• Maintain high standards for data quality, reliability, and performance.
• Stay up to date on advancements in data engineering and the DataOps technology stack to support continuous improvement.

Requirements and qualifications

• Experience in data engineering and data operations.
• Software engineering experience with microservices, messaging/streaming (Kafka), API integration, and stream processing.
• Proven hands-on experience with SQL, Python, PySpark, and Databricks.
• In-depth knowledge of CI/CD platforms and processes (e.g., Azure DevOps, GitLab, etc.).
• Experience with cloud data platforms (Azure preferred).
• Proven ability to produce rigorous, clear, and comprehensive documentation and communications.
• Familiarity with database design.
• Excellent problem-solving skills and an eye for detail.
• Effective communication and collaboration skills.

Personal characteristics

• Responsible and reliable, especially during critical periods of operation.
• Thorough and methodical in documentation and process development.
• Motivated and goal-oriented.
• Curious, enthusiastic, creative, and proactive.
• Passionate about analytics and technology, with a strong desire to learn and grow.
• Fluent in spoken and written English.