Summary: Our client seeks a DataOps Engineer to design, implement, and operate technologies and frameworks, enabling efficient and governed deployment of data and ML solutions. Highlights: 1. Key role in designing and implementing data and ML solution frameworks 2. Focus on reliable, secure, and automated data and analytics environments 3. Collaborate with Data Engineering, ML Engineering, and DevOps teams Client: Our client is a leading airline in Latin America. Project overview: The Advanced Analytics department drives the strategic use of data and analytics to create sustainable value across the organization. It develops data products and platforms that enable machine learning, generative AI, and advanced analytics capabilities, integrated transversally with business areas. * Position overview: Our client is looking for a DataOps Engineer who will play a key role in designing, implementing, and operating the technologies, frameworks, and environments that enable Data Engineering and Data Science teams to develop and deploy their solutions efficiently, with proper governance and at scale. * This role focuses on building reliable, secure, and automated data and analytics environments and ensuring that modern DataOps and MLOps practices are embedded across workflows. * Responsibilities: Design and maintain infrastructure, tools, and frameworks that support the creation and operation of data and analytical pipelines. * Ensure the scalability, reliability, and observability of data and analytics platforms. * Collaborate with Data Engineering, ML Engineering, and DevOps teams to promote best practices in DataOps and MLOps. * Develop automation solutions for data ingestion, orchestration, and monitoring in analytical and ML workflows. * Implement data governance, quality controls, and versioning practices within operational processes. * Contribute to evaluating and deploying new tools, architectures, and technologies that strengthen the overall data ecosystem. * Requirements: Experience with Google Cloud Platform (GCP) and its data and ML services (BigQuery, Dataflow, Pub/Sub, Cloud Composer, Vertex AI). * Strong knowledge of Infrastructure as Code (Terraform), containerization (Docker), and CI/CD automation. * Experience developing or integrating data platforms and tools such as Airflow, dbt, MLflow, Great Expectations, etc. * Ability to design secure, observable, and scalable solutions for data and analytics environments. * Experience working in agile, cross‑functional teams. * Fluent in Spanish * Good spoken English (intermediate level for documentation and collaboration) Nice to have: Knowledge of Python and data processing frameworks, with a focus on enabling environments for other technical teams.