Lead Data Engineer-PySpark, RedShift, Airflow, AWS

Lead Data Engineer Candidate should have 12+ years of experience in Data Engineering. Must have strong work experience with onshore-offshore model Designing, creating, testing and maintaining the complete data management & processing systems. Candidate need to have in depth understanding of how data pipelines are built Typical challenges with fetching data from various sources. How incremental/CDC data flows are handled. How do you ensure data quality How do you do Data profiling Hands-on experience with PySpark, Redshift (SQL) and Airflow at minimum Strong hands-on with required tech skills, flexible, right attitude to play the lead role Should be able to design and document data model at various levels Working closely with the stakeholders Building highly scalable, robust & fault-tolerant systems Knowledge of Hadoop ecosystem and different frameworks inside it – HDFS, YARN, MapReduce, Apache Pig, Hive, Flume, Sqoop, ZooKeeper, Oozie, Impala and Kafka Must have experience on SQL-based technologies (e.g. MySQL/ Oracle DB) and NoSQL technologies (e.g. Cassandra and MongoDB) Should have Python/Scala/Java Programming skills Discovering data acquisitions opportunities Finding ways & methods to find value out of existing data Improving data quality, reliability & efficiency of the individual components & the complete system Zortech Solutions