4 Aws Sns Jobs

6+ years of hands on experience with AWS services(Lambda, DynamoDB, SQS, SNS, S3, ECS, EC2) (mandatory in each service) Created lambda functions and done scripting Only deployment experience will not work Hands on Java, Spring Boot, Microservices, Kafka.

Summary As a Senior Dot Net Architect [18+ years ] at Gainwell, you can contribute your skills as we harness the power of technology to help our clients improve the health and well-being of the members they serve a communitys most vulnerable. Connect your passion with purpose, teaming with people who thrive on finding innovative solutions to some of healthcares biggest challenges. Here are the details on this position. Your role in our mission 18+ years of relevant architect experience required, especially in large-scale web applications. Experience with technical product configuration, design, and/or integration Comprehensive knowledge of object-oriented concepts with emphasis on .NET specifications, framework, .Net Core+ and design patterns using C# Experienced in building event driven applications and CQRS pattern. Experience in building ASP.Net Core Web application using MVC or Razor pages. Experience in building applications using ASP.Net Core WebApi, gRPC or GraphQL Experience in implementing SSO in ASP.Net Core Web and WebApi applications using OIDC or OAuth Should have experience in working with any of the messaging systems like RabbitMQ, AWS SNS, Kafka or Azure Service Bus Should have experience in working with distributed caching using Redis. Experience in developing applications using either Azure or AWS services. Create library of standard architecture artifacts. To work on feasibility of auto generating artifacts. Architecture Artifacts are configuration items and should be under change control - store in Github possibly. Basic Qualifications Bachelor's degree in computer science, information systems, or related field preferred An ability to work independently across multiple projects, and to meet deadlines. Experience in US Healthcare is beneficial . Must have a sound understanding of the software development and software test lifecycle. Certifications (Nice to have) TOGAF AWS Solution Architect ITIL Foundations What you should expect in this role Fast-paced,challenging and rewarding work environment. Work life balance. Hybrid office environment Will require late evening work to overlap US work hours.

Position Summary: S.E Analyst demonstrates expertise in data engineering technologies with the focus on engineering, innovation, strategic influence and product mindset. This individual will act as a key contributor of the team to design, build, test and deliver large-scale software applications, systems, platforms, services or technologies in the data engineering space. This individual will have the opportunity to work directly with partner IT and business teams, owning and driving major deliverables across all aspects of software delivery. The candidate will play a key role in automating the processes on Databricks and AWS. They collaborate with business and technology partners in gathering requirements, develop and implement. The individual must have strong analytical and technical skills coupled with the ability to positively influence the delivery of data engineering products. The applicant will be working in a team that demands innovation, cloud-first, self-service-first, and automation-first mindset coupled with technical excellence. The applicant will be working with internal and external stakeholders and customers for building solutions as part of Enterprise Data Engineering and will need to demonstrate very strong technical and communication skills. Job Description & Responsibilities: The candidate will be responsible to deliver business needs end to end from requirements to development into production. Through hands-on engineering approach in Databricks environment, this individual will deliver data engineering toolchains, platform capabilities and reusable patterns. The applicant will be responsible to follow software engineering best practices with an automation first approach and continuous learning and improvement mindset. The applicant will ensure adherence to enterprise architecture direction and architectural standards. The applicant should be able to collaborate in a high-performing team environment, and an ability to influence and be influenced by others. Experience Required: More than 6 months to 1.5 years of experience in software engineering, building data engineering pipelines, middleware and API development and automation Experience Desired: Expertise in Agile software development principles and patterns Expertise in building streaming, batch and event-driven architectures and data pipelines Primary Skills: Experience in messaging systems such as Apache ActiveMQ, WebSphere MQ, Apache Artemis, Kafka, AWS SNS Proficient in self-testing of applications, unit testing and use of mock frameworks, test-driven development (TDD) Knowledge on Behavioral Driven Development (BDD) approach (Spark or Scala) with Aws, Python Additional Skills: Ability to perform detailed analysis of business problems and technical environments Strong oral and written communication skills Ability to think strategically, implement iteratively and estimate financial impact of design/architecture alternatives Continuous focus on an on-going learning and development AWS Certifications - nice to have Devops, CI/CD, Databricks

Position Summary: S.E Lead Analyst demonstrates expertise in data engineering technologies with the focus on engineering, innovation, strategic influence and product mindset. This individual will act as key contributor of the team to design, build, test and deliver large-scale software applications, systems, platforms, services or technologies in the data engineering space. This individual will have the opportunity to work directly with partner IT and business teams, owning and driving major deliverables across all aspects of software delivery. The candidate will play a key role in automating the processes on Databricks and AWS. They collaborate with business and technology partners in gathering requirements, develop and implement. The individual must have strong analytical and technical skills coupled with the ability to positively influence the delivery of data engineering products. The applicant will be working in a team that demands innovation, cloud-first, self-service-first, and automation-first mindset coupled with technical excellence. The applicant will be working with internal and external stakeholders and customers for building solutions as part of Enterprise Data Engineering and will need to demonstrate very strong technical and communication skills. Job Description & Responsibilities: The candidate will be responsible to deliver business needs end to end from requirements to development into production. Through hands-on engineering approach in Databricks environment, this individual will deliver data engineering toolchains, platform capabilities and reusable patterns. The applicant will be responsible to follow software engineering best practices with an automation first approach and continuous learning and improvement mindset. The applicant will ensure adherence to enterprise architecture direction and architectural standards. The applicant should be able to collaborate in a high-performing team environment, and an ability to influence and be influenced by others. Experience Required: More than 6-8 years of experience in software engineering, building data engineering pipelines, middleware and API development and automation More than 3 years of experience in Databricks within an AWS environment Experience Desired: Expertise in Agile software development principles and patterns Expertise in building streaming, batch and event-driven architectures and data pipelines Primary Skills: Cloud-based security principles and protocols like OAuth2, JWT, data encryption, hashing data, secret management, etc. Expertise in Big data technologies such as Spark, Hadoop, Databricks, Snowflake, EMR, Glue Good understanding of Kafka, Kafka Streams, Spark Structured streaming, configuration-driven data transformation and curation Expertise in building cloud-native microservices, containers, Kubernetes and platform-as-a-service technologies such as OpenShift, CloudFoundry Experience in multi-cloud software-as-a-service products such as Databricks, Snowflake Experience in Infrastructure-as-Code (IaC) tools such as terraform and AWS cloudformation Experience in messaging systems such as Apache ActiveMQ, WebSphere MQ, Apache Artemis, Kafka, AWS SNS Experience in API and microservices stack such as Spring Boot, Quarkus, Expertise in Cloud technologies such as AWS Glue, Lambda, S3, Elastic Search, API Gateway, CloudFront Experience with one or more of the following programming and scripting languages Python, Scala, JVM-based languages, or JavaScript, and ability to pick up new languages Experience in building CI/CD pipelines using Jenkins, Github Actions Strong expertise with source code management and its best practices Proficient in self-testing of applications, unit testing and use of mock frameworks, test-driven development (TDD) Knowledge on Behavioral Driven Development (BDD) approach Additional Skills: Ability to perform detailed analysis of business problems and technical environments Strong oral and written communication skills