Responsibilities:
- Design, develop cloud based applications using Microsoft Azure and other Cloud platforms.
- Design, develop web applications, desktop applications using Microsoft technologies (.NET, C#, Microsoft Azure, IoTHub, WCF, WPF, SQL Server, Elastic DB, Redis).
- Work closely with onsite, offshore and cross functional teams, Product Management, UI/UX developers, Web and Mobile developers, SQA teams to effectively use technologies to build and deliver high quality and on-time delivery of Mobile Applications
- Proactively Identify risks and failure modes early in the development lifecycle and develop POCs to mitigate the risks early in the program
Requirements:
Education
- BE/ BTech degree in Computer Science or Electrical, Electronics with 5 to 8 plus years of software engineering and Mobile application development experience
- TECH/MCA/ MS degree in Computer Science or Electrical, Electronics with 4 to 6 plus years of software engineering experience
Required Technical Skills/Education:
- Excellent communication and leadership skills
- 3-5 years of Cloud software development experience under Agile development life cycle processes and tools
- Must have experience working with project management tools such as Jira, Rally, or TFS.
- Must have experience with source control tools like TFVC and/or Git
- Strong understanding of cloud technologies including SaaS, PaaS, and IaaS
- Develop messaging solutions using service bus queues, topics, relays, and notification hubs; create service bus namespaces and choose a tier; scale service bus
- Develop apps that use WS-federation, OAuth, and SAML-P endpoints
- Hands-on experience Implementing Redis caching, Azure Cache Services
- Hands-on design and implementation of transient fault handling for services, respond to throttling, Application Request Routing (ARR) affinity
- Troubleshoot and resolve concurrency issues in database
- Design always on, availability groups, geographical fault tolerant highly available database solutions
- Good Hands on experience diagnosing performance bottlenecks, wait stats, SQL query monitoring, review and optimization strategies
- Thorough experience in cache and non-relational databases like Cosmos DB etc.
- Hands-on development using distributed logging frameworks like serilog and diagnostics/dashboards using application insights.
- Sound knowledge and hand-on experience using Application lifecycle management, DevOps, CI and CD using TFS and Team services
- Hands on experience designing cloud applications for resilience and availability.
- Create normalized and highly scalable logical and physical database design and switch between different database technologies like Oracle, SQL Server, Elastic databases to low end databases like SQLLite
- Measure latencies, query execution times and propose and drive database/query optimization techniques
- Mobile first approach in designing applications and strong TDD fundamentals
- Thorough understanding of the Microsoft IOT suite including IOT Hubs, Event Hubs, Stream analytics, Machine learning, Notification Hubs etc.
- Hands on porting experience in atleast one IOT stacks on the embedded devices and at least one wireless and wired sensor/telemetry devices integration with cloud.
- Thorough knowledge and hands-on developing ARM templates and PowerShell scripts.
- Good understanding of the IOS/Android App submission and integration needs and impact on the cloud development
- Assertive communication, leadership and team skills
Preferred Technical Skills/Education:
- Experience with Building Automation and/or HVAC domain
- Knowledge on capabilities of cloud platforms like AWS, Google App Engine, VM Cloud, Orange etc.
- Good understanding of the Linux, AIX, Windows Operating systems, evolution and differences.
- Good understanding on Windows 7, Windows 8, 8.1 and 10 desktop apps, store apps etc.
- Experience in designing big data applications, interactive solutions, big data real time processing solutions, cognitive services, Data lake analytics, Hadoop/HDInsight, Machine learning and Microsoft analytics platform, machine learning and end to end cloud analytics
- Knowledge in data science
- Additional Comments