111 Dataops Jobs

Responsibilities: As a Machine Learning (ML) Operations Software Engineer within the Operational Artificial Intelligence team you will be responsible for deploying and maintaining machine learning systems in production reliably and efficiently. You will work as part of a team and will be responsible for managing and monitoring production ML systems for their operations, performance and effectiveness. You will be expected to follow processes and practices that allow for scalable deployment of ML models and solutions to production that automate various stages of machine learning life cycle from data collection, preparation, transformation, train, validation, serve and monitor. • Design and bui...

Role Overview: Lead and develop an international team of data experts to deliver advanced analytics solutions. Own the design and implementation of scalable DataOps pipelines and modern data architecture. Serve as a consultant, mentor, and enabler to internal stakeholders and other data teams. Drive digitalization and operationalization of data and AI initiatives across Siemens Mobility. Key Responsibilities: Team Leadership & Development Lead an international team of 10 data experts, fostering high performance and continuous learning. Mentor and enable internal customers and other data teams to leverage analytics solutions. Create visibility for team activities, communicate successes, and d...

As an AI Architect at Adyog, you will design, develop, and deploy real-world machine learning systems to advance AI and machine learning solutions to scale. You have operationalized machine learning while building scalable, robust, and secure products. You are a keen problem solver, utilizing technology to work out complex analytical problems. Your qualifications include: - Exposure to different stages of machine learning system design and development - Utilization of tools for machine learning pipeline management and monitoring such as MLflow, Pachyderm, Kubeflow, Seldon, Grafana - Familiarity with automation and deployment technologies like CircleCI, Jenkins, GitHub actions, etc., and infr...

Sales Director / Senior BDM - Data Engineering/Analytics - USA Exp: 10+ Years Industry: Digital, IT Services, Data Domain (End-Clients): Technology, E-Commerce /Retail, BFSI, Healthcare or Manufacturing. Functional Area: Digital Solutions: DevOps, Cloud, Data, DataOps, AI/ML, Analytics, Mobility, Application Development, Testing Solutions. Must Have: Travelled to US Sales Strategy and Planning Account Management Data Mining & Analytics Relationship Building Data-driven Decision Making Customer Needs Analysis Team Leadership Cloud Solution selling Responsibilities: Data centric solutions/use cases like Customer 360, Data Analytics, BI Reporting/Dashboards, Data Platform, Document AI along wit...

As a highly skilled DataOps Technical SME, your role will involve deploying and supporting DataOps platforms such as HighByte, Litmus, EMQX, and HiveMQ within manufacturing environments. You will be responsible for translating manufacturing business requirements into technical solutions, supporting solution architecture, and delivering scalable IIoT DataOps applications across multiple sites. Key Responsibilities: - Lead the design, development, and rollout of DataOps applications using platforms such as HighByte, Litmus, EMQX, HiveMQ, and similar technologies. - Collaborate closely with manufacturing stakeholders to translate business requirements into technical specifications and solutions...

As a Technical Project Manager(Data) with 13+ years of overall IT experience and at least 6 years of experience in a similar role, your responsibilities will include: - Owning the end-to-end delivery of data platform, AI, BI, and analytics projects, ensuring alignment with business objectives and stakeholder expectations. - Developing and maintaining comprehensive project plans, roadmaps, and timelines for data ingestion, transformation, governance, AI/ML models, and analytics deliverables. - Leading cross-functional teams including data engineers, data scientists, BI analysts, architects, and business stakeholders to deliver high-quality, scalable solutions on time and within budget. - Defi...

Job Title - ODS Technical & CoE Lead Location - Noida 62 Experience - 8+ Years Job Summary: Lead governance, standards, and operational excellence for the ODS (Operational Data Store) platform . Define data policies, enforce best practices, and drive performance, automation, and continuous improvement across data engineering teams. Key Responsibilities: Establish ODS governance framework for data quality, lineage, metadata, and access control. Build and manage ODS Center of Excellence (CoE) for standardization and automation. Collaborate with Data Architects, ETL Developers, and DBAs to ensure platform reliability and scalability. Monitor ODS performance, optimize ETL pipelines, and ensure S...

Senior Data Architect (Snowflake | SAP | Cloud), Snowflake, SAP BW/ECC, and Cloud platforms (AWS, Azure, GCP),10+ years of experience in Data Architecture, ETL/ELT, and DataOps Location: Ernakulam/Trivandrum(hybrid) Contract-3 months

Sr. Data Architect (10+ yrs) with strong Snowflake & SAP BW/ECC expertise. Lead data architecture, ETL, migration & governance. Drive scalable solutions, data modeling & performance optimization. Share resume on careers@successr.in Required Candidate profile Seeking 10+ yrs experienced data architect skilled in Snowflake, SAP BW/ECC, ETL, cloud data platforms & ABAP Strong in data modeling, migration, governance & team leadership. SnowPro certs preferred.

Role Overview: As a Healthcare Analytics Specialist based in Gurugram with 3 to 5 years of experience, your primary responsibility is to develop, maintain, and optimize data pipelines. This includes handling the ingestion, transformation, and loading of data from both internal and external sources. Collaborating with Operations is crucial to designing scalable, secure, and high-performing data workflows. Implementing best practices in data governance, version control, security, and documentation is essential for ensuring efficient operations. Key Responsibilities: - Building and maintaining analytical models for cost, quality, and utilization metrics using tools such as Python, R, or SQL-bas...

Will be responsible for the design development and administration of data management solutions that align with the business needs of the organization. Will also respond to support Operations specially on production tickets and business requests for access and reporting. Overall 5+ years of experience and has at least 2-3 years of experience in Data Engineering especially ADF Python PySpark SparkSql Sql and Databricks programming and cloud data ingestion data pipelines handling structured and semi-structured data formats like JSON XML. Collaborate with internal and external personnel including senior management system architects software developers database administrators design analysts and ...

Experience: 8+ years in data management, ODS/DWH operations, or data governance with proven leadership in CoE setup and cross-functional coordination. Overview: Lead governance, standards, and operational excellence for the ODS platform. Define and enforce data policies, drive best practices, and optimize performance, automation, and continuous improvement across data engineering teams. Key Responsibilities: Establish and maintain an ODS governance framework covering data quality, lineage, metadata, and access control. Build and manage the ODS Center of Excellence (CoE) for standardization, automation, and process improvement. Collaborate with Data Architects, ETL Developers, and DBAs to ens...

Technical i. Pyspark Spark SQL SQL and Glue. ii. AWS cloud experience iii. Good understanding of dimensional modelling iv. Good understanding DevOps CloudOps DataOps CI/CD & with a SRE mindset v. Understanding of Lakehouse and DW architecture vi. strong analysis and analytical skills vii. understanding of version control systems specifically Git viii. strong in software engineering APIs Microservices etc. Soft skills i. written and oral communication skills ii. ability to translate business needs to system

As a Data Engineer specializing in DataOps & Support, your role will involve a combination of technical troubleshooting, analytical problem-solving, and proactive management of data integrity issues within enterprise-scale data systems. Your primary focus will be on ensuring the health, reliability, and accuracy of critical data workflows that drive business operations. Key Responsibilities: - Proactively monitor data pipelines for Tune-In & Local reports to ensure ongoing reliability. - Analyze and debug data integrity issues, escalating bugs when necessary. - Troubleshoot DAG execution failures in different environments using tools such as Apache Airflow. - Create and maintain detailed doc...

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...

We are looking for 13+years experienced candidates for this role. Mode: Hybrid Preferred Location: Cochin/Trivandrum/Chennai Primary Skills : Overall 13+ Years of Experience in IT with 6+ years of experience as a Technical Product Manager, Technical Program Manager, or Delivery Lead. Hands-on development experience in data engineering, including data pipelines, ETL processes, and data integration workflows Proven track record managing data engineering, analytics, or AI/ML projects end to end Solid understanding of modern data architecture: data lakes, warehouses, pipelines, ETL/ELT, governance, and AI tooling Hands-on familiarity with cloud platforms (e.g., Azure, AWS, GCP) and DataOps/MLOps...

We are looking for 13+years experienced candidates for this role. Mode: Hybrid Preferred Location: Cochin/Trivandrum/Chennai Primary Skills : Overall 13+ Years of Experience in IT with 6+ years of experience as a Technical Product Manager, Technical Program Manager, or Delivery Lead. Hands-on development experience in data engineering, including data pipelines, ETL processes, and data integration workflows Proven track record managing data engineering, analytics, or AI/ML projects end to end Solid understanding of modern data architecture: data lakes, warehouses, pipelines, ETL/ELT, governance, and AI tooling Hands-on familiarity with cloud platforms (e.g., Azure, AWS, GCP) and DataOps/MLOps...

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...

We are seeking a highly skilled DataOps Technical SME with proven expertise in deploying and supporting DataOps platforms such as HighByte, Litmus, EMQX, and HiveMQ within manufacturing environments. The ideal candidate will have extensive experience translating manufacturing business requirements into robust technical solutions, supporting solution architecture and proposal development, and delivering scalable IIoT DataOps applications across multiple sites. Key Responsibilities: Lead the design, development, and rollout of DataOps applications using platforms such as HighByte, Litmus, EMQX, HiveMQ, and similar technologies. Work closely with manufacturing stakeholders to translate business...

In this role as a Data & AI Delivery Head, you will be responsible for leading end-to-end delivery of Data, AI/ML, and Advanced Analytics programs for global clients. Your expertise in data engineering, AI/ML, cloud platforms, and stakeholder management will be crucial for scaling delivery operations and building high-performance teams. **Key Responsibilities**: - **Delivery Leadership**: - Own end-to-end delivery for Data & AI programs across multiple clients. - Ensure projects are delivered on time, within budget, and aligned with business objectives. - Implement delivery best practices, governance frameworks, and agile methodologies. - **Client & Stakeholder Management**: - Act as the pri...

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...

Overview In this role, we are seeking a Senior Manager Offshore Program & Delivery Management to oversee program execution, governance, and service delivery across DataOps, BIOps, AIOps, MLOps, Data IntegrationOps, SRE, and Value Delivery programs. This role requires strong expertise in offshore execution, cost optimization, automation strategies, and cross-functional collaboration to drive operational excellence. Manage and execute DataOps programs, ensuring alignment with business objectives, data governance standards, and enterprise data strategy. Oversee real-time monitoring, automated alerting, and self-healing mechanisms to improve system reliability and performance. Develop and enforc...