Sr. Data Engineer

Architect, build, and maintain scalable, distributed data pipelines using Apache Spark and Microsoft Fabric to process large structured and unstructured datasets Integrate data from diverse internal and external systems, ensuring reliability, lineage, and consistency across the enterprise You are expected lead optimization of ETL/ELT workloads for large-scale analytics to improve cost efficiency, throughput, and reliability Define and implement standards for data quality, metadata management, cataloging, lineage, and governance compliance You will collaborate with data scientists, analysts, architects, and IT teams to define requirements, deliver insights, and integrate analytical models Develop and maintain comprehensive documentation for pipeline architectures, workflows, schemas, and operational processes You will be going to evaluate emerging technologies and introduce modern data engineering practices such as Lakehouse patterns, delta formats, automation, and real-time processing Lead resolution of complex data pipeline failures, ensuring platform stability, enterprise-grade reliability, and enforce data security, privacy, and access governance policies