Data Software Engineer

You should have 5-12 years of experience in Big Data & Data related technologies, with expertise in distributed computing principles. Your skills should include an expert level understanding of Apache Spark and hands-on programming with Python. Proficiency in Hadoop v2, Map Reduce, HDFS, and Sqoop is required. Experience in building stream-processing systems using technologies like Apache Storm or Spark-Streaming, as well as working with messaging systems such as Kafka or RabbitMQ, will be beneficial. A good understanding of Big Data querying tools like Hive and Impala, along with integration of data from multiple sources including RDBMS, ERP, and Files, is necessary. You should possess knowledge of SQL queries, joins, stored procedures, and relational schemas. Experience with NoSQL databases like HBase, Cassandra, and MongoDB, along with ETL techniques and frameworks, is expected. Performance tuning of Spark Jobs and familiarity with native Cloud data services like AWS or AZURE Databricks is essential. The role requires the ability to efficiently lead a team, design and implement Big data solutions, and work as a practitioner of AGILE methodology. This position falls under the category of Data Engineer and is suitable for individuals with expertise in ML/AI Engineers, Data Scientists, and Software Engineers.,