Lead Software Engineer

1 week ago


Gurgaon, Haryana, India Cvent Full time
Overview:

Cvent is a prominent player in the meetings, events, and hospitality technology sector, with over 4,800 employees and approximately 22,000 clients globally, which includes over half of the Fortune 500 companies. Founded in 1999, Cvent provides a full-fledged event marketing and management platform for marketers, event professionals, hotels, special event venues, and destinations seeking to elevate their group/MICE and corporate travel business. The company's technology facilitates the gathering of millions of individuals at events worldwide, revolutionizing the meetings and events industry through cutting-edge technology that fosters human connections. The backbone of Cvent is its people, with a culture that promotes intrapreneurship, empowering employees to think and act like entrepreneurs, encouraging risk-taking, and making decisions as if they were the founders of the organization. Cvent values the diverse perspectives each individual brings, cultivating a culture that embraces differences and capitalizes on shared connections.

About the position:

Cvent's Research and Development division is currently seeking an experienced and motivated Full-Stack Lead Software Engineer to join the Machine Learning & Data Science Group. The chosen candidate will play a crucial role in developing both front-end and back-end components of innovative data science toolkits and solutions. The ideal applicant should possess a profound grasp of JavaScript/TypeScript, React, Java, Python, and Infrastructure as Code. They should be a proactive self-starter capable of formulating practical solutions from vague requirements. An ability to design scalable, user-friendly, high-performance applications to operationalize data science R&D initiatives for internal teams and Cvent Products is essential. Collaboration with data scientists, data engineers, and software engineers to create, maintain, and provide support for data science R&D solutions is a key aspect of this role.

In This Role, You Will:
  • Contribute directly to designing, building, and maintaining efficient, secure, and reliable code powering both front-end and back-end components of data science solutions.
  • Demonstrate strong architectural and design skills collaborating with data scientists and cross-functional teams to drive the roadmap.
  • Assist consuming teams in adopting, upgrading, and utilizing the developed data science toolkits.
  • Stay abreast of emerging technologies and trends to anticipate future challenges and opportunities.
  • Develop responsive and user-friendly interfaces using modern web development frameworks.
  • Integrate all necessary security and data protection measures into the software development lifecycle.
  • Consistently seek ways to enhance the user experience of the data science toolkits by eliminating friction points.
Requirements:
  • Bachelors+ degree in Computer Science, Computer Engineering, or a related field, or equivalent work experience.
  • 7 to 9 years of Software Development experience.
  • Self-motivated with excellent troubleshooting abilities.
  • Highly skilled in at least one object-oriented language: Java or Python.
  • Proficient in JavaScript/TypeScript and React/Redux/Angular for web application development.
  • Familiarity with CI/CD concepts and managing pipelines for efficient software deployment.
  • Experience with RESTful Web Services and API development using Spring/Dropwizard or similar frameworks.
  • Knowledge of architecture and design principles including Design Patterns, Non-Functional Requirements (NFRs), and Cloud Computing platforms such as AWS/GCP/Azure.
  • Proven track record of excelling in a fast-paced, agile environment with a focus on results.
Preferred Skills:
  • Experience with databases like SQL Server, Snowflake, Couchbase, AWS DynamoDB, or other NoSQL technologies.
  • Familiarity with JavaScript/TypeScript and React/Redux/Angular for web application development.
  • Understanding of data science concepts, machine learning pipelines, and collaboration with data scientists.
  • Familiarity with the Databricks ML platform.


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