Data Engineer III

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Engineer III based in India. This role sits within a data engineering team responsible for building the pipelines, infrastructure, and automation that power advanced machine learning products. You will work with large-scale datasets and distributed systems in an environment processing extremely high volumes of events. The position combines hands-on engineering with collaboration across Data Science, Product, and Engineering teams. You will design reliable services, automate model deployment workflows, and continuously improve production data systems. The role offers exposure to cloud technologies, streaming platforms, orchestration tools, and modern machine learning infrastructure. You will contribute to systems that enable data scientists and users to analyze and act on complex data efficiently. This is a fully remote opportunity for experienced engineers based in India, with a strong focus on scalability, automation, and innovation.

Design and build scalable data services and pipelines that support machine learning products and data-intensive applications. Develop automation tools that enable data scientists to deploy, train, and evaluate models efficiently. Maintain, monitor, and improve production data systems, with a focus on reliability, scalability, and performance. Work with distributed systems and large-scale data processing environments to support high-volume workloads. Collaborate with product managers, data scientists, and engineers across multiple teams to deliver internal and external-facing services. Participate in code reviews, pull requests, engineering discussions, and other software development practices. Build and maintain CI/CD workflows and automated infrastructure following engineering best practices. Contribute to containerized development and orchestration using technologies such as Docker and Kubernetes. Apply AI technologies to improve decision-making, streamline workflows, increase efficiency, and support business outcomes. Collaborate across teams responsible for different aspects of machine learning data and infrastructure. Requirements Bachelor’s degree in Computer Science or a related technical field. 7+ years of relevant professional engineering experience. Strong knowledge of several relevant technologies, such as AWS, Python, Golang, Kafka, Airflow, Docker, Linux, and Kubernetes. Demonstrated experience working with very large volumes of data and building scalable data processing systems. Solid understanding of distributed system architecture, including key design considerations and trade-offs. Strong knowledge of CI/CD principles and software delivery best practices. Practical experience with Docker and/or Kubernetes-based development and orchestration. Proven experience using AI technologies to enhance decision-making, automate workflows, improve efficiency, or drive measurable business outcomes. Strong problem-solving and collaboration skills, with the ability to work effectively across technical and cross-functional teams. Experience creating automated and scalable infrastructure or data pipelines is highly valued. Familiarity with open-source contribution through platforms such as GitHub, technical blogs, or Stack Overflow is a plus. Additional experience with Spinnaker, relational databases, key-value stores, Spark, AWS Batch, EMR, Glue, or SageMaker is advantageous. Previous experience in cybersecurity, intelligence, or related technical domains is a plus. Benefits Competitive compensation and equity opportunities. Comprehensive physical and mental wellbeing programs. Competitive vacation and paid time-off policies. Paid parental and adoption leave. Professional development opportunities across career levels and roles. Employee networks, geographic community groups, and volunteering opportunities. Remote working flexibility for candidates based in India. Opportunities to work with large-scale data, AI, machine learning, and cloud technologies. Collaborative environment focused on innovation, experimentation, and continuous learning. Recognition as a globally certified Great Place to Work organization.

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