Skills: · Advanced working knowledge and experience with relational and non-relational databases. · Experience building and optimizing Big Data pipelines, architectures, and datasets. · Strong analytic skills related to working with structured and unstructured datasets. · Hands-on experience in Azure Databricks utilizing Spark to develop ETL pipelines. · Strong proficiency in data analysis, manipulation, and statistical modeling using tools like Spark, Python, Scala, SQL, or similar languages. · Strong experience in Azure Data Lake Storage Gen2, Azure Data Factory, Databricks, Event Hub, Azure Synapse. · Familiarity with several of the following technologies: Event Hub, Docker, Azure Kubernetes Service, Azure DWH, API Azure, Azure Function, Power BI, Azure Cognitive Services. · Azure DevOps experience to deploy the data pipelines through CI/CD. Qualifications and Experience: · Minimum 5-7 years of practical experience as Data Engineer. Bachelor’s degree in computer science, software engineering, information technology, or a related field. · Azure cloud stack in-production experience. Show more Show less
AEM DevOps Engineer - Job Description Airline Domain Experience needed Responsibilities AEM Infrastructure Management: Design, deploy, and maintain secure, scalable, and highly available AEM environments (author, publish, and dispatcher) across development, staging, and production systems. Automation & CI/CD: Develop and manage automated CI/CD pipelines using tools like Jenkins, GitLab CI, or Cloud Manager to streamline AEM deployments and reduce release cycles. Monitoring & Performance Optimization: Implement robust monitoring, logging, and alerting systems (e.g., New Relic) to proactively identify performance issues, ensure high availability, and optimize system performance. Cloud & Containerization: Deploy and manage AEM and supporting applications on cloud platforms (AWS, Azure) using containerization and orchestration tools such as Docker and Kubernetes. Security & Compliance: Apply security best practices including role-based access control, secure dispatcher configuration, SSL, and vulnerability assessments to maintain compliance with organizational and industry standards. Cross-functional Collaboration: Collaborate with AEM developers, system administrators, QA, and business teams to troubleshoot infrastructure issues, optimize configurations, and ensure seamless integration with enterprise systems. Backup & Disaster Recovery: Design and implement comprehensive backup, restore, and disaster recovery strategies for AEM environments to ensure business continuity. DevOps & Agile Enablement: Promote DevOps culture by supporting automation, agile workflows, continuous improvement, and efficient collaboration between development and operations. Requirements Qualifications 3+ years of hands-on experience as a DevOps Engineer or similar role managing Adobe Experience Manager environments. Strong understanding of AEM architecture (6.5+), including author/publish topology, dispatcher setup, performance tuning, and upgrade/patching strategies. Experience with cloud platforms (AWS, Azure), including deployment, scaling, and automation. Hands-on experience with Docker and Kubernetes for container orchestration. Expertise in CI/CD pipeline management using Jenkins, GitLab, or AEM Cloud Manager. Proficiency with scripting languages such as Bash, or PowerShell. Familiarity with monitoring tools such as Nagios, or New Relic. Strong understanding of networking, load balancing, and security in cloud and hybrid environments. Comfortable working in Agile teams and supporting DevOps practices. Preferred Qualifications Experience with AEM as a Cloud Service and cloud-native deployment models. Familiarity with Adobe Marketing Cloud tools (Analytics, Target, Campaign). Relevant cloud certifications (e.g., AWS Certified Solutions Architect, Azure DevOps Engineer Expert). Experience implementing high availability and disaster recovery strategies for AEM. Advanced knowledge of AEM Dispatcher configuration and performance tuning
Skills Advanced working knowledge and experience with relational and non-relational databases. Experience building and optimizing Big Data pipelines, architectures, and datasets. Strong analytic skills related to working with structured and unstructured datasets. Hands-on experience in Azure Databricks utilizing Spark to develop ETL pipelines. Strong proficiency in data analysis, manipulation, and statistical modeling using tools like Spark, Python, Scala, SQL, or similar languages. Strong experience in Azure Data Lake Storage Gen2, Azure Data Factory, Databricks, Event Hub, Azure Synapse. Familiarity with several of the following technologies: Event Hub, Docker, Azure Kubernetes Service, Azure DWH, API Azure, Azure Function, Power BI, Azure Cognitive Services. Azure DevOps experience to deploy the data pipelines through CI/CD. Qualifications And Experience Minimum 5-7 years of practical experience as Data Engineer. Bachelor’s degree in computer science, software engineering, information technology, or a related field. Azure cloud stack in-production experience.
Skills Advanced working knowledge and experience with relational and non-relational databases. Experience building and optimizing Big Data pipelines, architectures, and datasets. Strong analytic skills related to working with structured and unstructured datasets. Hands-on experience in Azure Databricks utilizing Spark to develop ETL pipelines. Strong proficiency in data analysis, manipulation, and statistical modeling using tools like Spark, Python, Scala, SQL, or similar languages. Strong experience in Azure Data Lake Storage Gen2, Azure Data Factory, Databricks, Event Hub, Azure Synapse. Familiarity with several of the following technologies: Event Hub, Docker, Azure Kubernetes Service, Azure DWH, API Azure, Azure Function, Power BI, Azure Cognitive Services. Azure DevOps experience to deploy the data pipelines through CI/CD. Qualifications And Experience Minimum 5-7 years of practical experience as Data Engineer. Bachelors degree in computer science, software engineering, information technology, or a related field. Azure cloud stack in-production experience. (ref:hirist.tech)
JD for SAP IS-Retail MM 5-6 years in SAP Retail Knowledge of Business process across, Fashion, Hard Goods and Food Experience in implementing large and complex SAP Projects and designing solutions to meet business requirements. Experience in working with business process/activity owners in understanding business requirement and solution design Experience in changes with SAP S4 HANA in Retail preview. Should have good Experience in Retail Master data like Merchandise hierarchy, Article hierarchy, Article master, Article categories and site master etc., Should have good Experience in Assortment & Layout Management, Pricing & Valuation. Procurement, Internal procurement. Inventory management, Goods receipt and Issue handling, Goods Issue via Outbound process, Physical Inventory and Cross Docking. Inventory & Warehouse Management, Handling Unit Management, merchandise distribution, replenishment planning various P2P processes. Integration Knowledge - Multiple SAP module such as Finance and Accounting, Inventory, warehouse Management and sales and distribution etc., Well versed in SAP Best Practice to accelerate delivery of SAP Projects and reduce Project cost. Experience in carrying out Fit gap analysis and Creating RICEF’s for business improvements, User exit and interface etc., Good Knowledge of EDI Interfaces of interfacing with Third Party Systems, Ecommerce Platforms and with Principal. Experience in suggesting solution automation in the business process. Support Experience of managing day-to-day IDOC monitoring, troubleshooting and adherence to SLAs for incidents. Good Consulting Skills and should be able to independently handle business users and stakeholders. Worked in Multilanguage environment Experienced in Customs Process and Taxation
As a Data Engineer in our team, you will be responsible for assessing complex new data sources and quickly turning these into business insights. You will also support the implementation and integration of these new data sources into our Azure Data platform. You are detailed in reviewing and analyzing structured, semi-structured, and unstructured data sources for quality, completeness, and business value. Your role involves designing, architecting, implementing, and testing rapid prototypes that demonstrate the value of the data and presenting them to diverse audiences. Additionally, you will participate in early-stage design and feature definition activities. Your responsibilities include implementing a robust data pipeline using the Microsoft Databricks Stack and creating reusable and scalable data pipelines. Collaboration is key as you will work as a team player, collaborating with members across multiple engineering teams to support the integration of proven prototypes into core intelligence products. Strong communication skills are required to effectively convey complex data insights to non-technical stakeholders. In terms of skills, you should have advanced working knowledge and experience with relational and non-relational databases, API data providers, and building and optimizing Big Data pipelines, architectures, and datasets. Strong analytic skills related to working with structured and unstructured datasets are necessary. Hands-on experience in Azure Databricks utilizing Spark to develop ETL pipelines is essential. Proficiency in data analysis, manipulation, and statistical modeling using tools like Spark, Python, Scala, SQL, or similar languages is required. Experience in Azure Data Lake Storage Gen2, Azure Data Factory, Databricks, Event Hub, Azure Synapse is preferred. Familiarity with technologies such as Event Hub, Docker, Azure Kubernetes Service, Azure DWH, API Azure, Azure Function, Power BI, Azure Cognitive Services is a plus. Knowledge of Azure DevOps to deploy data pipelines through CI/CD is beneficial. For qualifications and experience, a minimum of 5-7 years of practical experience as a Data Engineer is required. A Bachelor's degree in computer science, software engineering, information technology, or a related field is preferred. Experience with the Azure cloud stack in-production is necessary for this role.,
You will be responsible for developing and maintaining Connected TV (CTV) applications across various platforms such as Samsung Tizen, LG webOS, and Android TV. Your primary focus will be on creating high-performance, media-driven applications that offer a seamless and engaging user experience for OSN's video streaming services. Collaboration with the UX/UI team, product managers, and backend engineers will be essential to ensure optimal app performance, user experience, and integration with OSN's content platforms. Key responsibilities include developing and maintaining CTV apps for platforms like Tizen, webOS, and Android TV, ensuring a seamless user experience through collaboration with the UX/UI team, integrating third-party APIs for video streaming and user authentication, optimizing app performance for smooth playback and fast load times, implementing analytics tracking for user behavior analysis, working with backend engineers to efficiently utilize APIs and backend services, adhering to platform-specific development guidelines, and troubleshooting and resolving performance, crash, and playback issues. It is expected that you have a minimum of 5+ years of experience in Connected TV (CTV) app development for platforms like Tizen, webOS, Fire TV, or Android TV. Hands-on experience in front-end development using JavaScript (ES6), React or React Native, and frameworks specific to CTV platforms is required. Additionally, you should have a solid understanding of Android TV, Samsung Tizen, and LG WebOS, as well as experience with CTV platform emulators and developer tools such as Tizen Studio, LG webOS TV SDK, and Android TV Emulator. Experience with media streaming protocols like HLS and DASH, familiarity with DRM technologies (e.g., Widevine, PlayReady), integration with RESTful APIs for content streaming, working with Git in an Agile/Scrum environment, familiarity with video-on-demand (VOD) or OTT services, knowledge of CI/CD practices, automated testing, and modern deployment strategies are also necessary. Strong problem-solving skills, knowledge of SOLID Principles and design patterns, familiarity with Agile/Scrum methodologies and tools like Jira, and excellent communication and interpersonal skills are preferred. In terms of knowledge and skills, a strong understanding of CTV platforms such as Samsung Tizen, LG webOS, Fire TV, and Android TV, proficiency in JavaScript (ES6), React, HTML5, CSS3, JavaScript, XML & JSON, expertise in React principles, media streaming protocols, DRM technologies, performance optimization, integrating with APIs, managing backend services, video codecs, CI/CD pipelines, automated testing, and debugging platform-specific issues are essential. The ability to work independently, take ownership of projects, and deliver high-quality code is also expected.,