DataOps Engineer

1 week ago


Bengaluru, India Neemtree Full time

Responsibilities :- Promote a DataOps approach to Data science, engineering, and analytics delivery processes to automate the provision of data, testing, and monitoring, and shorten CI/CD.- Collaborate with data & ML leads and create and build an optimal data pipeline architecture for the data solutions, including data science products.- Ensure the data pipelines are scalable and performant, as well as create and maintain a service to connect data products.- Create dashboards and other tools required to efficiently monitor our data and ML infrastructure, pipelines, ETL, and analytics delivery processes.- Building an end-to-end event instrumentation and alerting system to detect and alert to any anomaly in the system or in the data.- Assist in managing our data and ML infrastructure (upgrading, monitoring, optimising).- Collaborate with IT DevOps engineers and participate in enterprise DevOps activities.- Exchange your knowledge on infra and data standards with other developers and be part of our tech community. Promote the use of engineering best practices.- Contribute to innovative POCs with our data & engineering teams.- Remain flexible towards technology approaches to ensure that the best advantage is being taken by new technologies.Requirements :- Strong drive to solve problems, communicate clearly, and contribute positively to a DevOps/DataOps culture.- Knowledge of the latest DevOps tools and practices.- Experience with data pipelines within AWS (Glue, DataPipeline, Athena, EMR, DMS, Spark).- Experience with Database Replication and databases like Aurora, MySQL, MariaDB, etc.- Efficient in building CI/CD pipelines for containerized Java/Python codestack.- Comfortable with Git workflow.- Experience with applications deployed in AWS.- Experience with configuration management and provisioning tools (e. g., Ansible, CloudFormation, Terraform).- Knowledge of one or more scripting languages - Orchestration/containerisation using Docker and Kubernetes.- Basic knowledge of data science & ML engineering.- Bachelor's Degree in computer science or a similar degree, or Big Data Background from top-tier universities.- Experience: 8+ years of experience. (ref:hirist.tech)


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