Big Data Developer

As a Big Data Engineer, your role will involve understanding and familiarity with all Hadoop Ecosystem components and Hadoop Administrative Fundamentals. You should have experience working with NoSQL in at least one of the data stores such as HBase, Cassandra, or MongoDB. Additionally, you should be proficient in HDFS, Hive, and Impala. You will need to have experience with schedulers like Airflow, Nifi, etc. Your responsibilities will include developing standardized practices for delivering new products and capabilities using Big Data technologies, encompassing data acquisition, transformation, and analysis. It will be essential for you to define and develop client-specific best practices around data management within a Hadoop environment on Azure cloud. Monitoring health, tuning, and growth of on-premises and cloud databases will also be part of your tasks. You should have experience in managing security and maintenance of snowflake databases, as well as monitoring user access to the snowflake database. Hands-on exposure to ETL using Snowflake native services and SQL & scripting is required. You must possess a good understanding of Snowflake internals and integration of Snowflake with other data processing and reporting technologies. Designing and developing ETL pipelines in and out of the data warehouse using Snowflakes Snow SQL will be a key responsibility. You should have a deep understanding of relational as well as NoSQL data stores methods and approaches like star and snowflake dimensional modeling. Experience in designing and deploying virtual warehouse, schema, views, zero-copy clone in Snowflake cloud data warehouse is necessary. It would be beneficial to have experience working with AWS services like Lambda, S3, DynamoDB, Glue, etc. Qualifications Required: - 5-10 years of relevant experience in Big Data technologies and related fields - Proficiency in Hadoop Ecosystem components and Hadoop Administrative Fundamentals - Experience with NoSQL data stores such as HBase, Cassandra, or MongoDB - Hands-on experience with schedulers like Airflow, Nifi, etc. - Prior experience in managing security and maintenance of databases, including snowflake databases - Strong understanding of Snowflake internals and integration with other data processing and reporting technologies - Knowledge of relational and NoSQL data stores methods and approaches like star and snowflake dimensional modeling - Experience in designing and deploying virtual warehouse, schema, views, zero-copy clone in Snowflake cloud data warehouse - Good to have experience working with AWS services like Lambda, S3, DynamoDB, Glue, etc. As a Big Data Engineer, your role will involve understanding and familiarity with all Hadoop Ecosystem components and Hadoop Administrative Fundamentals. You should have experience working with NoSQL in at least one of the data stores such as HBase, Cassandra, or MongoDB. Additionally, you should be proficient in HDFS, Hive, and Impala. You will need to have experience with schedulers like Airflow, Nifi, etc. Your responsibilities will include developing standardized practices for delivering new products and capabilities using Big Data technologies, encompassing data acquisition, transformation, and analysis. It will be essential for you to define and develop client-specific best practices around data management within a Hadoop environment on Azure cloud. Monitoring health, tuning, and growth of on-premises and cloud databases will also be part of your tasks. You should have experience in managing security and maintenance of snowflake databases, as well as monitoring user access to the snowflake database. Hands-on exposure to ETL using Snowflake native services and SQL & scripting is required. You must possess a good understanding of Snowflake internals and integration of Snowflake with other data processing and reporting technologies. Designing and developing ETL pipelines in and out of the data warehouse using Snowflakes Snow SQL will be a key responsibility. You should have a deep understanding of relational as well as NoSQL data stores methods and approaches like star and snowflake dimensional modeling. Experience in designing and deploying virtual warehouse, schema, views, zero-copy clone in Snowflake cloud data warehouse is necessary. It would be beneficial to have experience working with AWS services like Lambda, S3, DynamoDB, Glue, etc. Qualifications Required: - 5-10 years of relevant experience in Big Data technologies and related fields - Proficiency in Hadoop Ecosystem components and Hadoop Administrative Fundamentals - Experience with NoSQL data stores such as HBase, Cassandra, or MongoDB - Hands-on experience with schedulers like Airflow, Nifi, etc. - Prior experience in managing security and maintenance of databases, including snowflake databases - Strong understanding of Snowflake internals and integration with other data processing and reporting technologies - Knowledge of relational and NoSQL