Search the 6 jobs at BrandMuscle

The Senior Software Engineer builds tools for clients, interprets business requirements, develops detailed specifications, builds data and process components, and integrates components into products for testing and release to customers.

Support Engineer II / Senior Support Engineer at Brandmuscle in Bangalore / Noida. Responsibilities include handling client custom projects, support existing applications, configuration changes on client sites, backend data modifications, SSIS package builds, report generation, troubleshooting, and advanced tasks like SSIS package creation, PowerShell scripting, and C# coding.

The Quality Assurance Analyst (QAA) works with the development teams to design, build, and install new applications, develop and execute test plans, review test results, report defects, and contribute to automation testing. The role requires 2-5+ years of relevant experience with QA Automation, proficiency in Selenium with C# / Java, experience in automation frameworks, knowledge of languages like JavaScript and HTML, and an understanding of Microsoft Test Manager, JIRA, SQL, and APIs.

Design, develop, test, and implement solutions in NodeJS, AngularJs, and databases. Collaborate with team members to ensure timely delivery of work to stakeholders. Bring a global mindset and excellent communication skills. Be an energetic and innovative engineer with a passion for technology.

The Manager, Product Management is responsible for developing the strategic vision and executing the product roadmap of the BrandMuscle local marketing platform. This includes the full product management life-cycle: persona research, competitive analysis, analyst briefings, requirements authoring, pricing, go-to-market, and sales support. The Manager, Product Management will partner with teams across the organization to become an expert on the market, design a world-class solution, build the value proposition, and ultimately drive sales growth.

The Data Scientist will analyze data to provide insights for product and marketing teams, support model creation, and recommend improvements to data collection methods. They will cleanse and verify data integrity and need strong statistical knowledge along with proficiency in data science tools.