Role Overview :

As a Data Engineer at Rayosys Services, you will be responsible for architecting and maintaining the data infrastructure that powers our clients' analytical and operational platforms. You will work closely with cross-functional teams, including data scientists, product managers, and software engineers, to design efficient data pipelines and ensure the seamless flow of information across the enterprise. Your work will directly influence the reliability and accessibility of data, enabling stakeholders to make informed, data-driven decisions that drive business growth and operational efficiency.

Key Responsibilities :

- Design and implement scalable ETL/ELT pipelines to ingest, process, and transform large volumes of structured and unstructured data for downstream analytics.

- Develop and optimize data models to support complex business requirements and ensure high performance of data warehousing solutions.

- Integrate real-time data streaming services using Kafka to support low-latency data processing needs across various business units.

- Maintain and scale distributed data storage systems, including MongoDB, to ensure high availability and data integrity for critical applications.

- Collaborate with infrastructure teams to containerize data applications using Docker, facilitating consistent deployment across development and production environments.

- Monitor and troubleshoot data pipeline performance, proactively identifying bottlenecks and implementing optimizations to improve throughput and reliability.

- Partner with stakeholders to translate business requirements into technical specifications, ensuring that data architecture aligns with long-term organizational goals.

Required Skillset :

- Demonstrated expertise in Python and Java for building robust data processing applications and automation scripts.

- Advanced proficiency in SQL for complex query optimization and database management within large-scale environments.

- Proven ability to design and manage cloud-based data architectures on AWS, leveraging native services for storage, compute, and orchestration.

- Strong understanding of Big Data ecosystems and the ability to handle high-velocity data streams effectively.

- Excellent analytical and problem-solving skills, with the ability to communicate complex technical concepts to non-technical stakeholders clearly.

- Ability to thrive in a collaborative, fast-paced environment across multiple locations including Navi Mumbai, Pune, Delhi NCR, Indore, Hyderabad, Gurgaon/Gurugram, and Noida.

- A minimum of 6 to 12 years of professional experience in data engineering or a related field, with a track record of delivering end-to-end data solutions.