Sr Data Engineer

Ability to lead, mentor, and guide a team of data engineers, ensuring best practices in coding, architecture, and deployment. In addition, high people management skills that encourage professional growth and foster a culture of learning and collaboration. Data Engineering skills Experience in building and maintaining an enterprise Data Lakes and\or Data Warehouses. Design and implementation of data pipelines that handle both structured and semi-structured data. Deep understanding in one of the cloud platforms (e.g., AWS, Azure, GCP) and their associated data storage and compute solutions (e.g., Amazon S3, Azure Blob Storage, Databricks, EC2, Lambda). Strong experience in managing cloud resources and scaling them based on workloads. hands-on experience with big data frameworks like Apache Spark and Flink. Ability to architect and optimize distributed data processing frameworks for high-throughput and low-latency workloads. Expertise in real-time data processing using technologies such as Apache Kafka, Apache Flink, and low latency Database engines. Able to design and manage real-time streaming pipelines and integration with batch processing frameworks. Desired Skills Experience in Building Delta Lakehouse solution using Databricks. Advanced skills in optimizing Apache Spark for performance at scale, including fine-tuning Spark configurations, caching strategies, partitioning, and debugging slow-running jobs. Programming Languages Python, Java (a plus) and SQL. Strong knowledge of data libraries and frameworks (e.g., PySpark .. ) and the ability to implement custom solutions for data transformations, batch jobs, and pipeline automation.