Data Engineer

Company Description Rhevix helps businesses transform ideas into intelligent, scalable, and impactful technology solutions. The company combines AI, data, cloud engineering, and technology consulting to modernize operations, unlock data value, and accelerate digital transformation. Rhevix delivers AI and Generative AI solutions, data engineering and analytics, cloud architecture and modernization, intelligent automation, custom software development, and end-to-end consulting. By partnering closely with clients, Rhevix designs secure, scalable, and future-ready solutions aligned with strategic goals, from concept and strategy through implementation. At Rhevix, technology is engineered not only to address current challenges but also to create new possibilities for the future.
Role Description This is a full-time, on-site Data Engineer role based in the Pune Division. The Data Engineer will design, build, and maintain scalable data pipelines and ETL processes to support analytics, reporting, and AI-driven solutions. Daily responsibilities include developing and optimizing data models, implementing and managing data warehouses, and ensuring data quality, security, and reliability across systems. The role involves collaborating with data analysts, data scientists, and software engineering teams to understand requirements and translate them into robust data architectures. The Data Engineer will also monitor data infrastructure performance, troubleshoot issues, and contribute to continuous improvement of Rhevix’s data platforms and best practices.
Qualifications
Strong data engineering skills, including experience with modern data platforms and distributed data processing.
Solid understanding of data modeling and data warehousing to design efficient, scalable data structures.
Hands-on experience with Extract Transform Load (ETL) processes and tools for building reliable data pipelines.
Ability to apply data analytics concepts to support reporting, dashboards, and advanced analytics use cases.
Proficiency in SQL and at least one programming language commonly used in data engineering (such as Python or Scala).
Experience with cloud data services (e.g., AWS, Azure, or GCP) and modern data stack tools is highly beneficial.
Familiarity with data governance, security, and best practices for handling sensitive and large-scale data.
Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field, or equivalent practical experience.
Ability to collaborate in cross-functional teams, communicate clearly with technical and non-technical stakeholders, and adapt to evolving project needs.

Work arrangement
No