Ai Data Engineer

or have led significantbusiness journeys for top brands Indian and global brands. Enhance Your Leadership Acumen. Join the journey to create global scale and World Best. Challenge Yourself to do something path breaking. Be Empowered. The only thing to stop you will be your imagination. Travel space is likely to see significant growth. Witness and shape this space. It will be one exciting journey. Own a wide portfolio of our Platform Business, India. Primary focus will be on top talent attraction, retention, development, and engagement. Talent Acquisition, Business HR, HR Operations & Leaning will report in apart from relevant COE functions connected to these domains. Key Responsibilities : Design, develop, and maintain data pipelines and ETL workflows using Apache Spark and AWS Glue. Build and optimize large-scale data lake solutions leveraging HDFS, Apache Hudi, and AWS S3. Develop and manage data ingestion frameworks, transformations, and data modeling for analytical workloads. Design & Develop AI / ML pipelines using pyspark, LLM, Langchain, RAG to solve business usecases. Enable data discovery and querying using AWS Athena and other analytical tools. Implement and monitor data quality, security, and governance practices across the data platform. Work closely with DevOps and Cloud teams to ensure data infrastructure is reliable, secure, and cost-efficient. Required Skills & Experience : 5–8 years of hands-on experience in Data Engineering or related roles. Strong proficiency in Apache Spark (PySpark / Scala) and AWS Glue. Solid understanding of HDFS, Data Lake architectures, and distributed data processing. Hands-on experience with Apache Hudi for incremental data processing and time-travel capabilities. Experience in AWS ecosystem — S3, Athena, Lambda, IAM, EMR, etc. Strong SQL skills and experience with query optimization. Good understanding of data modeling, ETL design patterns, and data lifecycle management. Familiarity with version control (Git) and CI / CD processes for data pipelines. Exposure to building an end-to-end data science solution is a plus