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The role involves backend development primarily with Ruby on Rails, while also supporting frontend enhancements using React. You'll collaborate with different teams to design features, build analytics tools, and maintain existing applications. Participation in the entire development cycle following Agile processes is required, along with innovative problem-solving and quality-driven work.

As a Tech Lead Ruby on Rails Developer, you'll provide leadership, design solutions, and mentor engineers. You'll work collaboratively on high-impact projects, focusing on quality, innovation, and technical excellence in software development. Success in this role requires strong communication skills and a deep understanding of business goals to influence engineering priorities.

The Senior Data Engineer will design and manage large-scale data solutions, ensuring scalability and high performance. This role includes mentoring junior engineers, collaborating with Agile teams, and exploring new technologies to optimize data infrastructure.

As a React Lead Engineer, you will develop and maintain frontend components using React and TypeScript, collaborating with backend engineers and UX/UI teams to build user-friendly interfaces for data-heavy applications, while implementing dynamic query handling and reusable components.

The Data Engineer will collaborate with Business Analyst and Data Science teams to integrate new data sources, implement data lake solutions on AWS, and enhance the organization's data ecosystem, ensuring standards for technical excellence and addressing data quality and governance concerns.

As a Data Engineer, you will be responsible for developing and maintaining data pipelines and ensuring data quality. You will use technologies like Python and SQL to support data modeling and ETL processes, contributing to data analytics initiatives within the organization.

The Lead Data Engineer will lead data teams and develop advanced analytics solutions to optimize data value for organizations. Responsibilities include collaborating with analysts, integrating data sources into a cloud ecosystem, implementing data lake solutions, and ensuring data quality and governance standards.