Senior Data Engineer – Remote Cloud & ML Infrastructure Expert

Join a globally recognized broadcasting enterprise as a Senior Data Engineer. You will be instrumental in developing high-performance data infrastructure and deploying scalable machine learning systems in production. This remote opportunity empowers you to architect cloud-native solutions, collaborate with data scientists, and shape intelligent platforms for millions of users worldwide. Key Responsibilities - Design and develop scalable, versioned data pipelines to support machine learning workflows. - Provide expert guidance to data science teams, focusing on deploying ML models into robust, high-availability production environments. - Build microservices for serving machine learning models via REST APIs, including health checks and monitoring hooks. - Ensure deployment readiness of services in cloud-native environments, meeting SLAs for uptime and performance. - Automate deployment using Infrastructure-as-Code principles (Terraform) within GCP ecosystems. - Optimize pipeline performance and manage data quality and lineage through tools like Airflow and MLflow. Required Skills - 5+ years of professional experience in Data Engineering or Software Engineering roles. - Advanced programming skills in Python and SQL; exposure to PySpark for big data processing. - Proven experience with Google Cloud Platform (GCP) services including BigQuery, BigTable, and Cloud Functions. - Strong hands-on experience with Docker, Kubernetes, and GitLab CI/CD for container orchestration and automation. - Solid understanding of data pipeline orchestration using Apache Airflow. - Familiarity with machine learning lifecycle tools such as MLflow, including model tracking and deployment. - Competency in designing and managing RESTful APIs for model serving. - Strong problem-solving skills, proactive communication, and the ability to work cross-functionally in distributed teams. Nice to Have - Experience with other public cloud platforms (AWS, Azure). - Exposure to Terraform for provisioning infrastructure in declarative code. - Knowledge of data versioning, data contracts, and schema evolution practices. - Prior work on media, telecom, or high-traffic B2C systems. - Contributions to open-source projects in the data engineering or ML infrastructure space. Why Join Us - Work on cutting-edge, high-impact systems in a multinational broadcasting company reaching millions daily. - Collaborate with talented engineers and data scientists in a dynamic, fast-paced environment. - Enjoy the freedom of a 100% remote role with flexible hours and global reach. - Gain access to enterprise-grade GCP environments, production-level ML pipelines, and modern DevOps tooling. This is more than a typical data engineering role—it's your chance to lead in production-scale ML deployment, shape intelligent infrastructure, and elevate global broadcasting technology.