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Mid-level generalist data role with broad Hadoop/Spark requirements increases applicant competition.
Core data engineering skills like SQL, Hadoop, and Spark are transferable across industries.
Multiple mandatory years of experience and specific Hadoop, Spark, and SQL skills narrow candidate pool.
Build and maintain high performance data applications across traditional (MySQL) and distributed (Hadoop, Spark) platforms with end-to-end responsibility for database processes and big data ETL lifecycle.
Administer, monitor, and optimize MySQL and Hadoop ecosystems including workflows with Oozie, Zookeeper, Sqoop, Hive, Impala, and manage big data cluster deployments on private and public cloud.
Support production systems integration of new algorithms, troubleshoot issues, deliver ad hoc business analysis, and ensure reliable data processing and backup routines.
Minimum 4+ years experience with SQL (MySQL) mandatory.
At least 2+ years hands-on experience with Cloudera Hadoop Distribution and Apache Spark.
Strong knowledge of RDBMS and distributed cloud platforms including database administration, performance tuning, and big data components like MapReduce, Hive, Impala, Kafka, HBase.
Bachelor’s degree or higher in Computer Science or equivalent; experience with BI tools (Looker Studio, Power BI, or equivalent) is must.
Experienced in full backend database development lifecycle including writing complex SQL queries, stored procedures, and managing distributed data workflows at scale.
Comfortable working with large structured and unstructured datasets using technologies like Apache Spark, Hadoop ecosystem, and cloud platforms.
Able to handle integration with engineering teams for deployment and support, with skills in data analytics tools and some exposure to advanced performance optimization and CI/CD pipelines.