Data Engineer

Design, develop, and maintain scalable ETL/data ingestion pipelines for processing large volumes of structured and unstructured data.Work extensively with SQL and NoSQL databases, particularly MongoDB, to support enterprise data platforms and analytics solutions by Tableau.Optimize database performance through query tuning, indexing, partitioning, and efficient data modeling techniques.Process, store, archive, and purge high-volume datasets while ensuring performance, scalability, and reliability.Develop high-performance data processing solutions using Python and PySpark.Implement and manage modern data lake/lakehouse architecture using open table formats such as Apache Iceberg and Delta Lake.Ensure data quality, integrity, validation, and governance across data pipelines and storage systems.Build and maintain interactive Tableau dashboards and visualizations for business and operational reporting.Collaborate with cross-functional teams including business stakeholders, analysts, and engineering teams to deliver scalable data solutions.Work effectively within Agile/Scrum teams, participating in sprint planning, daily stand-ups, backlog grooming, code reviews, and iterative delivery cycles.