Agile Jobs in India

We are seeking a passionate Flutter Developer to join our team in Visakhapatnam. This role is perfect for candidates with up to 6 years of experience who are excited about building high-quality mobile applications.As a Flutter Developer, you will be responsible for developing and maintaining mobile applications using the Flutter framework. You will collaborate with designers and other developers to create smooth, efficient, and visually appealing apps. Additionally, you will troubleshoot and debug issues to ensure optimal functionality and performance.Key responsibilities include:1. **App Development**: Build and deploy mobile applications on both Android and iOS platforms using Flutter, ensuring a seamless user experience.2. **Collaboration**: Work closely with UI/UX designers to translate designs into high-quality code, ensuring that the application is visually appealing and user-friendly.3. **Testing and Debugging**: Identify and fix bugs in the application through rigorous testing, improving application performance and reliability.4. **Code Maintenance**: Write clean, maintainable, and efficient code, while also contributing to code reviews to uphold code quality standards.Candidates should have a degree in a relevant field and possess strong knowledge of Dart programming language and the Flutter framework. Familiarity with RESTful APIs, version control systems like Git, and good problem-solving skills are highly desirable. A passion for coding and continuous learning is essential in this dynamic role.

K9HR SOLUTIONS, Krishna Patel (Assistant Branch Manager - Mo. No. 98798 71629 Email ID: abm.rajkot@k9hr.com) is looking for Quality Test Engineer As Follows:Supervise wire & cable manufacturing processes (extrusion, stranding, insulation, etc.)Monitor production quality and ensure adherence to standardsHandle testing of cables (HV testing, insulation resistance, continuity, etc.)Troubleshoot electrical and production-related issuesMaintain and improve production efficiencyEnsure compliance with safety and quality standards (ISI, ISO, etc.)Coordinate with production, quality, and maintenance teamsMaintain documentation and reports for production and testingKnowledge of wire & cable manufacturing processesUnderstanding of electrical testing methodsFamiliar with industry standards (ISI, IEC, ISO)Strong problem-solving and analytical skillsBasic knowledge of machinery used in cable manufacturingGood communication and teamwork skills

Job PurposeThe Senior Software Developer (Golang) is responsible for designing, developing, and maintaining scalable, high-performance system. The role focuses on development using Golang while adhering to modern software engineering practices, security standards, and Agile methodologies.Key ResponsibilitiesDesign, develop, and maintain using GolangDevelop robust, scalable, and high-performance backend servicesApply Go best practices including goroutines, channels, templating, and code generationWork with Go frameworks, routers, and dependency management toolsPerform unit testing and TDD in an Agile/Scrum environmentEnsure software quality through code reviews, linting, and static code analysisOptimize performance using profiling and monitoring toolsCollaborate with cross-functional teams including product, testing, and operationsContribute to system design using established design principles and patternsParticipate in troubleshooting, root cause analysis, and production support when requiredRequired QualificationsBachelors or Masters degree in: oComputer ScienceoInformation TechnologyoElectronics & CommunicationoMCAExperience5+ years of hands-on experience Technical SkillsPrimary SkillsGolang programming (advanced proficiency)Linux and Windows operating systems (advanced knowledge) . Better understanding of Golang EcosystemSoftware Engineering PracticesObject-Oriented ProgrammingSecure coding and SCA toolsUnit testing and TDDAgile/Scrum methodologies

Influences, Coaches & Mentors Team Members On Agile Practices & Principles.removes Impediments to the Team's Progress; Escalate Obstacles Requiring Outside Resolution. Identifies Risks & Issues that Might have An Impact On Delivery. Prioritize Work.

Role: Quality Assurance Engineer (Data & API)SUMMARYThe Quality Assurance Engineer partners with Engineering, Data, and Developmentteams to ensure client requirements are implemented correctly and reliably acrosshighvolume data pipelines. This role reviews requirements, designs test strategies, andexecutes automated and manual validation-emphasizing shiftleft practices andrepeatable automation. Candidates are former developers or Software DevelopmentEngineer in Test (SDET) who can effectively test large datasets, craft complex SQL fordata comparisons, and collaborate within a single, shared sprint cadence.ESSENTIAL DUTIES AND RESPONSIBILITIES Configure, implement, and maintain automated testing frameworks for data and APIvalidation (DBT tests, Pytest, SQL validators). Translate JIRA user stories and acceptance criteria into comprehensive test plans,scenarios, and data validation scripts. Ensure requirements traceability by mapping test cases and validation scriptsdirectly to client requirements and acceptance criteria, maintaining cleardocumentation throughout the lifecycle. Design and execute unit, integration, smoke, regression, and endtoend tests alignedto the recommended QA & automation framework. Validate large datasets for completeness, accuracy, timeliness, lineage, and schemaconformance, author complex SQL for data comparison. Coordinate with Engineering to enable shiftleft testing - QA participates ingrooming, planning, and daily standups; quality is a shared responsibility. Assist with user acceptance testing (UAT) and production validation, includingpostrelease smoke testing and regression cycles. Analyze test outputs, identify defects, document issues, and drive rootcauseanalysis; champion environment parity (VAL mirrors PROD). Contribute to release governance: freeze windows, QA gates, rollback plans, andrelease logs; ensure test evidence is captured. Continuously improve tools, templates, and processes; propose JIRA automation toautocreate QA stories from engineering stories. Develop domain knowledge of client data products, pipelines, integrations, and KPIs. Maintain comprehensive test documentation, including test cases, scripts, andresults, to support audits and compliance. Conduct performance and security testing as required to ensure robust, scalable,and secure solutions. Advocate for user experience and usability in all testing activities.AGILE & COLLABORATION EXPECTATIONS Active participant in Agile ceremonies (grooming, planning, standups, demos, retros)within a single, shared sprint cadence. Story readiness includes defined test criteria and data availability; QA estimatestracked alongside development. Promote predictable velocity by integrating automated tests into CI; definition ofdone includes -tested and validated.- Stay current with emerging QA tools, technologies, and best practices; proactivelyrecommend improvements to processes and frameworks.REQUIRED QUALIFICATIONS Former software developer or SDET with handson coding experience (Pythonpreferred). Expertise in SQL and relational databases; able to design complex validationqueries for large datasets. Demonstrated experience testing data pipelines, ETL/ELT workflows, and APIs inhighvolume environments. Practical knowledge of Airflow (or similar orchestration), DBT, and CI systems;experience validating DAG executions. Proficiency with automated testing tools (Selenium/Cucumber/Playwright for UIwhere applicable; Pytest for services; DBT for data). Proficiency with version control systems (e.g., Git) and defect tracking tools (e.g.,Jira, Azure DevOps). Experience with JIRA and Agile development methodology; comfortable with sharedsprint delivery. Strong critical thinking; challenges ambiguous requirements and drives clarity inacceptance criteria. Excellent communication skills; able to partner with Product Owners and Engineersto define testable stories.PREFERRED / DOMAIN EXPERIENCE Experience with liveevent data, broadcast schedules, media assets, or fanengagement platforms. Experience with bigdata validation (Snowflake/BigQuery/Redshift) and performancetesting of queries at scale. Familiarity with API contract testing, data lineage tools, and dataset comparisonframeworks. ISTQB or equivalent certification is a plus. Experience with cloud-based data platforms (AWS, Azure, GCP) is a plus.

Key Responsibilities Model Development: Lead the design and development of quantitative data engineeringmodels, including algorithms, data pipelines, and data processing systems, to supportbusiness requirements. Data Processing: Develop and maintain data processing pipelines to ingest, clean,transform, and aggregate large volumes of data from various sources, ensuring dataquality and reliability. Algorithm Development: Design and implement algorithms for data analysis, machinelearning, and statistical modeling, using techniques such as regression analysis,clustering, and predictive modeling. Performance Optimization: Identify and implement optimizations to improve theperformance and efficiency of data processing and modeling algorithms, consideringfactors like scalability and resource utilization. Data Visualization: Create visualizations of data and model outputs to communicateinsights and findings to stakeholders. Data Quality Assurance: Implement data quality checks and validation processes toensure the accuracy, completeness, and consistency of data used in models andanalyses. Model Evaluation: Evaluate the performance of data engineering models using metricsand validation techniques, and iterate on models to improve their accuracy andeffectiveness. Collaboration: Collaborate with data scientists, analysts, and business stakeholders tounderstand requirements, develop models, and deliver insights that drive businessdecisions. Documentation: Document the design, implementation, and evaluation of dataengineering models, including assumptions, methodologies, and results, to ensurereproducibility and transparency. Continuous Learning: Stay updated with the latest trends, tools, and technologies inquantitative data engineering and data science, and continuously improve your skillsand knowledge.Desired Skills and Experience Data Engineering: Strong background in data engineering principles, including dataingestion, data processing, data transformation, and data storage, using tools andframeworks such as Apache Spark, Apache Flink, or AWS Glue. Quantitative Analysis: Proficiency in quantitative analysis techniques, includingstatistical modeling, machine learning, and data mining, with experience inimplementing algorithms for regression analysis, clustering, classification, and predictivemodeling. Programming Languages: Proficiency in programming languages commonly used fordata engineering and quantitative analysis, such as Python, R, Java, or Scala, as well asexperience with SQL for data querying and manipulation. Big Data Technologies: Familiarity with big data technologies and platforms, such asHadoop, Apache Kafka, Apache Hive, or AWS EMR, for processing and analyzing largevolumes of data. Data Visualization: Experience in data visualization techniques and tools, such asMatplotlib, Seaborn, or Tableau, for creating visualizations of data and model outputs tocommunicate insights effectively. Machine Learning Frameworks: Familiarity with machine learning frameworks andlibraries, such as PyTorch for implementing and deploying machine learning models. Cloud Computing: Experience with cloud computing platforms, such as AWS, Azure, orGoogle Cloud Platform, and proficiency in using cloud services for data engineering andmodel deployment. Software Development: Strong software development skills, including proficiency insoftware design patterns, version control systems (e.g., Git), and software testingframeworks, to develop robust and maintainable code. Problem-solving Skills: Excellent problem-solving skills, with the ability to analyzecomplex data engineering and quantitative analysis problems, identify solutions, andimplement them effectively. Communication and Collaboration: Strong communication and collaboration skills, withthe ability to work effectively with cross-functional teams, including data scientists,analysts, and business stakeholders, to understand requirements and deliver solutions. Domain Knowledge: Domain knowledge in areas such as finance, healthcare, ormarketing, depending on the industry, to understand the context and requirements ofdata engineering models in specific domains. Continuous Learning: A commitment to continuous learning and staying updated withthe latest trends, tools, and technologies in data engineering, quantitative analysis, andmachine learning.

Key Responsibilities Analyst Workflows: Design and development of company integrated content publishing platform using a proprietary 3rd party editorial and publishing platform for integrated digital publishing. Designing and Developing APIs: Design and development of robust, scalable, and secure APIs on AWS, considering factors like performance, reliability, and cost-efficiency. AWS Service Integration: Integrate APIs with various AWS services such as AWS Lambda, Amazon API Gateway, Amazon SQS, Amazon SNS, AWS Glue, and others, to build comprehensive and efficient solutions. Performance Optimization: Identify and implement optimizations to improve performance, scalability, and efficiency, leveraging AWS services and tools. Security and Compliance: Ensure APIs are developed following best security practices, including authentication, authorization, encryption, and compliance with relevant standards and regulations. Monitoring and Logging: Implement monitoring and logging solutions for APIs using AWS CloudWatch, AWS X-Ray, or similar tools, to ensure availability, performance, and reliability. Continuous Integration and Deployment (CI/CD): Establish and maintain CI/CD pipelines for API development, automating testing, deployment, and monitoring processes on AWS. Documentation and Training: Create and maintain comprehensive documentation for internal and external users, and provide training and support to developers and stakeholders. Team Collaboration: Collaborate effectively with cross-functional teams, including product managers, designers, and other developers, to deliver high-quality solutions that meet business requirements. Problem Solving: troubleshooting efforts, identifying root causes and implementing solutions to ensure system stability and performance. Stay Updated: Stay updated with the latest trends, tools, and technologies related to development on AWS, and continuously improve your skills and knowledge. Desired Skills and Experience Development: 5+ years of extensive experience in designing, developing, and deploying using modern technologies, with a focus on scalability, performance, and security. AWS Services: proficiency in using AWS services such as AWS Lambda, Amazon API Gateway, Amazon SQS, Amazon SNS, Amazon SES, Amazon RDS, Amazon DynamoDB, and others, to build and deploy API solutions. Programming Languages: Proficiency in programming languages commonly used for development, such as Python, Node.js, or others, as well as experience with serverless frameworks like AWS. Architecture Design: Ability to design scalable and resilient API architectures using microservices, serverless, or other modern architectural patterns, considering factors like performance, reliability, and cost-efficiency. Security: Strong understanding of security principles and best practices, including authentication, authorization, encryption, and compliance with standards like OAuth, OpenID Connect, and AWS IAM. DevOps Practices: Familiarity with DevOps practices and tools, including CI/CD pipelines, infrastructure as code (IaC), and automated testing, to ensure efficient and reliable deployment on AWS. Problem-solving Skills: Excellent problem-solving skills, with the ability to troubleshoot complex issues, identify root causes, and implement effective solutions to ensure the stability and performance. Communication Skills: Strong communication skills, with the ability to effectively communicate technical concepts to both technical and non-technical stakeholders, and collaborate with crossfunctional teams. Agile Methodologies: Experience working in Agile development environments, following practices like Scrum or Kanban, and ability to adapt to changing requirements and priorities. Continuous Learning: A commitment to continuous learning and staying updated with the latest trends, tools, and technologies related to development and AWS services. Bachelor's Degree: A bachelor's degree in Computer Science, Software Engineering, or a related field is often preferred, although equivalent experience and certifications can also be valuable.