Senior Data Engineer; Lakehouse

As a Senior Data Engineer at our Bengaluru office, your role will involve designing, developing, and maintaining scalable data pipelines. You will be responsible for building and managing Data Lakehouse architecture using technologies such as Delta Lake, Iceberg, and Hudi. Your key responsibilities will include: - Processing large-scale datasets using PySpark and Apache Spark - Ingesting data from various sources such as APIs, databases, and streaming platforms into data lakes - Optimizing data workflows for performance, scalability, and reliability - Implementing data quality, validation, and governance frameworks - Collaborating with data scientists, analysts, and business teams - Developing and maintaining data models for analytics and reporting - Working with cloud platforms such as AWS, Azure, and GCP for data storage and processing - Monitoring and troubleshooting data pipelines and workflows You should have 610 years of experience in a similar role and be comfortable working in a hybrid work mode. Your expertise in data engineering, data lakes, PySpark, Apache Spark, and cloud platforms will be key in driving the success of our data projects. (Note: No additional details of the company were provided in the job description.) As a Senior Data Engineer at our Bengaluru office, your role will involve designing, developing, and maintaining scalable data pipelines. You will be responsible for building and managing Data Lakehouse architecture using technologies such as Delta Lake, Iceberg, and Hudi. Your key responsibilities will include: - Processing large-scale datasets using PySpark and Apache Spark - Ingesting data from various sources such as APIs, databases, and streaming platforms into data lakes - Optimizing data workflows for performance, scalability, and reliability - Implementing data quality, validation, and governance frameworks - Collaborating with data scientists, analysts, and business teams - Developing and maintaining data models for analytics and reporting - Working with cloud platforms such as AWS, Azure, and GCP for data storage and processing - Monitoring and troubleshooting data pipelines and workflows You should have 610 years of experience in a similar role and be comfortable working in a hybrid work mode. Your expertise in data engineering, data lakes, PySpark, Apache Spark, and cloud platforms will be key in driving the success of our data projects. (Note: No additional details of the company were provided in the job description.)