Full-stack Engineer

• Design, develop, and optimize database schemas, tables, indexes, and relationships to ensure efficient data storage and retrieval.
• Write complex SQL queries, stored procedures, triggers, and functions to support business and application requirements.
• Gather, clean, and process raw structured and unstructured data from multiple sources (APIs, relational DBs, distributed file systems).
• Design and implement ETL pipelines for data ingestion, transformation, and storage using MySQL, Hadoop, and Spark.
• Perform query optimization, indexing, and partitioning to improve database performance.
• Manage replication, clustering, and failover strategies to ensure high availability.
• Design and manage large-scale datasets using Hadoop ecosystem components (HDFS, MapReduce, Hive, Impala, Kafka, HBase, Pig).
• Build and maintain real-time streaming pipelines using Apache Spark and Spark Streaming.
• Collaborate with cross-functional engineering teams and DevOps to integrate scalable data solutions into production systems and support CI/CD.
• Take end-to-end responsibility for database lifecycle management (MySQL + Big Data ETL + Analytics).

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