54 Azure Iot Jobs - Page 3

About The Role : Primary Skills: I. Strong knowledge of IoT platforms and technologies, including sensor devices, gateways, communication protocols, and IoT frameworks. II. Expertise in designing and architecting scalable and secure IoT solutions. III. Proficiency in integrating IoT systems with cloud platforms (Azure IoT) IV. Understanding edge computing and analytics for real-time data processing and decision-making. V. IoT data management and storage knowledge, including databases, data lakes, and streaming platforms. VI. Familiarity with IoT security principles and best practices, including device authentication, encryption, and secure data transmission. VII. Experience designing IoT architectures that can handle large-scale deployments and high data volumes. Secondary Skills: VIII. Ability to design and implement IoT analytics solutions for extracting insights from sensor data. IX. Understanding IoT connectivity options, including cellular networks, Wi-Fi, and LPWAN (Low Power Wide Area Network). X. Proficiency in IoT integration with enterprise systems and applications, such as ERP, CRM, and supply chain management. XI. Knowledge of IoT data visualization and dashboarding tools for effective presentation of IoT insights. XII. Awareness of emerging IoT technologies and standards, such as edge AI, digital twins, and MQTT. Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.1. Applies scientific methods to analyse and solve software engineering problems.2. He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.3. His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.4. The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.5. The software engineer collaborates and acts as team player with other software engineers and stakeholders.

Project Role : Application Lead Project Role Description : Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have skills : Edge Computing Good to have skills : Kubernetes, Microsoft Azure IaaS Minimum 12 year(s) of experience is required Educational Qualification : BE/BTECH/MCA Project Role :Application LeadProject Role Description :Lead the effort to design, build and configure applications, acting as the primary point of contact. Must have Skills :Edge Computing, SSI: NON SSI:Good to Have Skills :SSI:Kubernetes, Microsoft Azure Architecture, Microsoft Azure IaaS NON SSI :Job Requirements :Key Responsibilities :Python or Go Embedded Linux C/C Application Containerization using Docker or Moby Machine learning, Deep learning and Artificial Intelligence on the Edge Computing HW Devices Experience in designing and developing end to end Edge Compute Solution Design and Development of distributed Edge Computing Solutions and services Leading the development activities and guiding the team on technical front in designing MEC based or pure on-premise HCI based Edge computing SolutionsReview of code andTechnical Experience :Experience designing Kubertnetes Clusters for EDGE COMPUTINGEdge Model Management and MonitoringExperience working on Nvidia Jetson or Intel Movidius Neural Compute Stick or Google Coral DevicesExperience in scalable inference services using OVMS, Triton ,DeepStreamExperience in designing and developing end to end Edge Compute Solution either using AWS IoT Green Grass or Azure IoT Gateway Solutions C or Java using OpenJDK on Embedded Linux or Yocto or ROS Experience in TensorFlow,PyTorch,OProfessional Attributes :Must have good communications skills and ability to manage the team membersMust be able to produce clear and concise documentation including requirements documents, design specs, status reports, system documentation and emailsMust have proven track record of technical leadership roles delivering sEducational Qualification:BE/BTECH/MCAAdditional Info :Connected Device Streaming data analytics Experience in Azure Stack Edge or AWS Snowball Edge Qualifications BE/BTECH/MCA

Project Role : Application Architect Project Role Description : Provide functional and/or technical expertise to plan, analyze, define and support the delivery of future functional and technical capabilities for an application or group of applications. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Must have skills : Manufacturing Operations Good to have skills : NA Minimum 12 year(s) of experience is required Educational Qualification : BTech BE Job Title:Industrial Data ArchitectSummary:We are seeking a highly skilled and experienced Industrial Data Architect with a proven track record in providing functional and/or technical expertise to plan, analyse, define and support the delivery of future functional and technical capabilities for an application or group of applications. Well versed with OT data quality, Data modelling, data governance, data contextualization, database design, and data warehousing.Must have Skills:Domain knowledge in areas of Manufacturing IT OT in one or more of the following verticals Automotive, Discrete Manufacturing, Consumer Packaged Goods, Life ScienceKey Responsibilities: Industrial Data Architect will be responsible for developing and overseeing the industrial data architecture strategies to support advanced data analytics, business intelligence, and machine learning initiatives. This role involves collaborating with various teams to design and implement efficient, scalable, and secure data solutions for industrial operations. Focused on designing, building, and managing the data architecture of industrial systems. Assist in facilitating impact assessment efforts and in producing and reviewing estimates for client work requests. Own the offerings and assets on key components of data supply chain, data governance, curation, data quality and master data management, data integration, data replication, data virtualization. Create scalable and secure data structures, integrating with existing systems and ensuring efficient data flow.Qualifications: Data Modeling and Architecture:oProficiency in data modeling techniques (conceptual, logical, and physical models).oKnowledge of database design principles and normalization.oExperience with data architecture frameworks and methodologies (e.g., TOGAF). Database Technologies:oRelational Databases:Expertise in SQL databases such as MySQL, PostgreSQL, Oracle, and Microsoft SQL Server.oNoSQL Databases:Experience with at least one of the NoSQL databases like MongoDB, Cassandra, and Couchbase for handling unstructured data.oGraph Databases:Proficiency with at least one of the graph databases such as Neo4j, Amazon Neptune, or ArangoDB. Understanding of graph data models, including property graphs and RDF (Resource Description Framework).oQuery Languages:Experience with at least one of the query languages like Cypher (Neo4j), SPARQL (RDF), or Gremlin (Apache TinkerPop). Familiarity with ontologies, RDF Schema, and OWL (Web Ontology Language). Exposure to semantic web technologies and standards. Data Integration and ETL (Extract, Transform, Load):oProficiency in ETL tools and processes (e.g., Talend, Informatica, Apache NiFi).oExperience with data integration tools and techniques to consolidate data from various sources. IoT and Industrial Data Systems:oFamiliarity with Industrial Internet of Things (IIoT) platforms and protocols (e.g., MQTT, OPC UA).oExperience with either of IoT data platforms like AWS IoT, Azure IoT Hub, and Google Cloud IoT Core.oExperience working with one or more of Streaming data platforms like Apache Kafka, Amazon Kinesis, Apache FlinkoAbility to design and implement real-time data pipelines. Familiarity with processing frameworks such as Apache Storm, Spark Streaming, or Google Cloud Dataflow.oUnderstanding of event-driven design patterns and practices. Experience with message brokers like RabbitMQ or ActiveMQ.oExposure to the edge computing platforms like AWS IoT Greengrass or Azure IoT Edge AI/ML, GenAI:oExperience working on data readiness for feeding into AI/ML/GenAI applicationsoExposure to machine learning frameworks such as TensorFlow, PyTorch, or Keras. Cloud Platforms:oExperience with cloud data services from at least one of the providers like AWS (Amazon Redshift, AWS Glue), Microsoft Azure (Azure SQL Database, Azure Data Factory), and Google Cloud Platform (BigQuery, Dataflow). Data Warehousing and BI Tools:oExpertise in data warehousing solutions (e.g., Snowflake, Amazon Redshift, Google BigQuery).oProficiency with Business Intelligence (BI) tools such as Tableau, Power BI, and QlikView. Data Governance and Security:oUnderstanding of data governance principles, data quality management, and metadata management.oKnowledge of data security best practices, compliance standards (e.g., GDPR, HIPAA), and data masking techniques. Big Data Technologies:oExperience in big data platforms and tools such as Hadoop, Spark, and Apache Kafka.oUnderstanding of distributed computing and data processing frameworks. Excellent Communication:Superior written and verbal communication skills, with the ability to effectively articulate complex technical concepts to diverse audiences. Problem-Solving Acumen:A passion for tackling intricate challenges and devising elegant solutions. Collaborative Spirit:A track record of successful collaboration with cross-functional teams and stakeholders. Certifications:AWS Certified Data Engineer Associate / Microsoft Certified:Azure Data Engineer Associate / Google Cloud Certified Professional Data Engineer certification is mandatory Minimum of 14-18 years progressive information technology experience. Qualifications BTech BE

Skill required: Data Scientist - Data Science Designation: I&F Decision Sci Practitioner Analyst Qualifications: Diploma In CS and Engineering Years of Experience: 3 to 5 years What would you do? Data & AIIn this role, you will be working on the interdisciplinary field about scientific methods, processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured. What are we looking for? Construct, design, and put into practice scalable data pipelines with PySpark, and other pertinent technologies Build and maintain data lakes and data warehouses, ensuring data quality, integrity, and availability Process and transform large datasets using PySpark to support analytics and business intelligence initiatives Develop and deploy Docker containers to package and manage data processing applications Work together to comprehend data requirements and provide solid data solutions with data scientists, analysts, and other stakeholders Monitor and optimize data pipelines for performance, scalability, and reliability Implement data governance and security practices to protect sensitive information Experience with Linux/Unix Systems and Scripting Experience with Version Control Systems, such as Git Knowledge on scheduling job using informatica ETL, and Autosys, as required Create and implement containerization using Kubernetes and orchestration using Docker containers for data processing application packaging and management Agility for quick learning Commitment to quality Written and verbal communication Adaptable and flexible Ability to work well in a team Roles and Responsibilities: Design and develop new data pipelines using Databricks notebooks and ADLS Gen2.0 to ingest and process raw data efficiently and ensuring reliability and scalability of the pipeline. Combines data gathering to model creation, use Databricks Notebooks to unify the process and instantly deploy to production. Integrates with a wide variety of data stores and services such as Azure SQL Data Warehouse, Azure Cosmos DB, Azure Data Lake Store, Azure Blob storage, Azure Event Hubs, Azure IoT Hub, and Azure Data Factory. Utilize Databricks and Delta/parquet tables to optimize the performance of both new and existing data processing pipeline to reduce job run time and improve efficiency. Maintain the data platform focusing on process monitoring, troubleshooting, and data readiness, ensuring high-quality data for regular reporting and system optimization. Work with other data engineers to design and implement enhancements to the overall data platform, improving functionality and performance. Work independently on end-to-end implementation of data processing pipelines, from development-testing-deployment using Databricks workflow. Should be proficient in PySpark operations to extract-transform-load data from/to Azure Delta Lake, creating reports to support business request to meet multiple priorities in given time. Qualifications Diploma In CS and Engineering