193 Dataops Jobs

As a Dataops Lead, you will be responsible for managing, design highly scalable and Available solution for data pipelines that provides the foundation for collecting, storing, modelling, and analysing massive data sets from multiple channels. Responsibilities: Align Sigmoid with key Client initiatives Interface daily with customers across leading Fortune 500 companies to understand strategic requirements Connect with VP and Director level clients on a regular basis. Travel to client locations Ability to understand business requirements and tie them to technology solutions Strategically support Technical Initiatives Design, manage & deploy highly scalable and fault-tolerant distributed compon...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

Key Responsibilities : - Design and implement end-to-end MLOps pipelines for continuous integration, continuous delivery, and continuous training (CI/CD/CT) of ML models. - Manage and optimize the production environment for ML models, using containerization (Docker) and orchestration (Kubernetes) to ensure scalability and reliability. - Implement monitoring and logging solutions to track model performance, data drift, and potential anomalies in production. - Collaborate with data scientists to transition models from research and development into a production-ready state. - Automate the retraining and redeployment of models to maintain accuracy and adapt to new data. - Troubleshoot and resolv...

As an Azure Data Factory Developer with a focus on Data Engineering, your role will involve designing and implementing end-to-end data solutions using Azure Data Factory (ADF). You will collaborate closely with stakeholders to gather requirements and build robust pipelines that drive analytics and business insights. Key Responsibilities: - Design and implement complex data pipelines in Azure Data Factory - Integrate data from various sources including on-prem databases, APIs, and cloud storage - Develop ETL/ELT strategies to manage both structured and unstructured data - Support data transformation, cleansing, and enrichment procedures - Implement logging, alerting, and monitoring mechanisms...

Seosaph-infotech is a rapidly growing company in customized software development, providing advanced technology solutions and trusted services across multiple business verticals. You will be responsible for the following key responsibilities: - Independently complete conceptual, logical and physical data models for any supported platform, including SQL Data Warehouse, Spark, Data Bricks Delta Lakehouse or other Cloud data warehousing technologies. - Govern data design/modelling documentation of metadata (business definitions of entities and attributes) and constructions database objects, for baseline and investment funded projects, as assigned. - Develop a deep understanding of the business ...

If you are someone who can lead and inspire teams while being hands-on with modern data technologies, apply to this position! Manager Data Engineering will work closely with Shure associates located in North America, Europe, and Asia to build, enhance, and maintain data and analytics solutions to meet the global business needs. Responsible for engineering and supporting data pipelines leveraging Shure technology investments in AWS, Informatica, Snowflake. Data will include structured and unstructured, internal, and external, Internet of Things, etc. This role requires exposure to industry best practices, technological trends, the willingness to learn new emerging technologies, and collaborat...

Overview If you are someone who can lead and inspire teams while being hands-on with modern data technologies, apply to this position! Manager Data Engineering will work closely with Shure associates located in North America, Europe, and Asia to build, enhance, and maintain data and analytics solutions to meet the global business needs. Responsible for engineering and supporting data pipelines leveraging Shure technology investments in AWS, Informatica, Snowflake. Data will include structured and unstructured, internal, and external, Internet of Things, etc. This role requires exposure to industry best practices, technological trends, the willingness to learn new emerging technologies, and c...

As a Senior Data Science & Advanced Analytics Leader, your main responsibility will be to drive data strategy, lead the design and development of scalable data solutions, and enable AI/ML-driven decision-making across the organization. You will oversee the end-to-end development lifecycle, manage high-performing teams, and collaborate closely with cross-functional stakeholders to enable data-driven product innovation and business impact. Key Responsibilities: - Lead the end-to-end architecture, development, and optimization of scalable data pipelines supporting AI/ML model deployment and analytics use cases. - Oversee Database and NoSQL data platforms (810+ years) including schema design, pe...

About Amgen Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what's known today. About The Role Role Description: We are seeking a seasoned Engineering Manager (Data Engineering) to lead the end-to-end management of enterprise data assets and operational data workflows. This role is critical in ensuring the availability, quality, con...

Job Purpose and Impact The Senior Professional, Cyber Engineering & Technology Operations job designs, builds, and governs productiongrade RPA / data pipelines that consume securityplatform APIs (Wiz, Defender, Tufin, etc.), embed AI/LLM (RAG) layers, and feed Azurebased analytics. This role operates within the organization with minimal supervision, while supporting operational efficiency. Key Accountabilities Architect endtoend bot & ETL workflows, embed AI/LLM (RAG) layers. Own CI/CD pipelines in Azure DevOps (Git repos, build/release libraries). Create reusable activity modules and datamodels for use by the team. Define test harnesses, linting, and monitoring for all automation artifacts....

Job Purpose and Impact The Professional, Cyber Engineering & Technology Operations job designs, builds, and governs productiongrade RPA / data pipelines that consume securityplatform APIs (Wiz, Defender, Tufin, etc.), embed AI/LLM (RAG) layers, and feed Azurebased analytics. This role operates within the organization with limited supervision, while supporting operational efficiency. Key Accountabilities Architect endtoend bot & ETL workflows, embed AI/LLM (RAG) layers. Own CI/CD pipelines in Azure DevOps (Git repos, build/release libraries). Create reusable activity modules and datamodels for use by the team. Define test harnesses, linting, and monitoring for all automation artifacts. Mentor...

Role Overview: As a Data Engineer - Principal at Birlasoft in Hyderabad, India, you will be responsible for leading Snowflake implementations, optimizing data pipelines, and providing technical leadership in cloud data architecture. With over 10 years of experience in data engineering, you will play a crucial role in designing scalable solutions and ensuring high performance and efficiency in data processing. Key Responsibilities: - Lead Snowflake implementation, including data modeling, warehouse design, and performance tuning. - Optimize SQL queries, stored procedures, and UDFs for high efficiency. - Implement Snowflake best practices such as clustering, partitioning, and zero-copy cloning...

Role Overview: You will be the technology leader responsible for spearheading the Scale AI service offering, driving enterprise-wide AI deployment with domain agents, MLOps, and responsible governance. Your role will involve architecting and delivering comprehensive AI solutions, from vertical applications to core platform infrastructure. Key Responsibilities: - Lead and scale the entire Scale AI service offering, aiming to achieve 40-60% productivity gains for clients. - Architect and oversee the development of AI Foundry platform components, including AgentSpace.ai, Govern.ai, and AutonomousDataEng.ai. - Define and execute the strategy for vertical AI applications across diverse personas a...