DescriptionWe are seeking a highly motivated and skilled DataOps Engineer to join our team. In this role, you will design, implement, and optimize data workflows and pipelines to ensure data availability, reliability, and scalability across the organization. You will collaborate with data engineers, data scientists, devops and IT teams to drive automation, and maintain the data infrastructure.Key Responsibilities:Data Pipeline Development and Maintenance:Ensure pipelines are scalable, efficient.Monitoring:Monitor data workflows to identify and resolve bottlenecks or failures.Automation and Optimization:Automate routine data processing tasks to increase efficiency.Optimize data workflows infrastructure for performance and cost-effectiveness.Collaboration:Work closely with data engineers, scientists, and analysts to understand requirements.Infrastructure Management:Manage and maintain on-premises data infrastructure.Ensure data storage solutions are secure, reliable, and meet compliance standards.Tooling and Technology:Implement and manage tools for data orchestration, monitoring, and visualization like Apache Airflow, or similar.Evaluate new technologies to improve existing workflows and architectures.Documentation:Document workflows, processes, and best practices for team reference and training.RequirementsProficiency in programming languages like Python and SQL.Experience with containerization tools like Docker and orchestration platforms like Kubernetes.Strong understanding of data pipeline tools like Apache Kafka, Airflow, Spark.Proficiency in CI/CD pipelines and DevOps practices.Knowledge of data governance, security, and compliance standards.Preferred Skills:Proficiency with version control tools like Gitlab.Experience with configuration management tools like Ansible or SaltStack.Familiarity with big data technologies.Understanding of machine learning workflows and data science tools.BenefitsTraining & DevelopmentPrivate Health Insurancebreakfast and lunchHybrid workplace