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Data Testing Coordinator – Regulatory Reporting & Data Validation (SQL/Python/Data Quality). Perform data reconciliation and validation. Conduct System of Record (SOR) analysis.
BigData and Hadoop Ecosystems, BigData and Hadoop Ecosystem - MapR. Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, Big Data model techniques using Python. Must have good experience working in large scale application development using Big Data ecosystem.
Utilize tools for continuous integration and continuous deployment (CI/CD), and Infrastructure as Code (IaC) like Terraform to automate and improve development and release processes. Develop scalable and robust code for large scale batch processing systems using Hadoop, Oozie, Pig, Hive, Map Reduce,
Mandatory Technical Skills Skills: PIG, Mapreduce, HDFS, HBase, Hive, YARN, SPARK, Impala, Kafka, Oozie, Java and shell scripting Strong hands on experience with Java, web-services and APIs Strong understanding of hadoop fundamentals Strong understanding of RDBMS concepts and experience with relatio
The ideal candidate should have a Bachelor's degree and at least 3 years of experience in Accounting, Finance, or Economics, combined with technical expertise in Python and SQL.
Strong understanding of RDBMS concepts and must have good knowledge of writing SQL and interacting with RDBMS and NoSQL database - HBase programmatically. Strong understanding of File Formats Parquet, Hadoop File formats. At least 5 years of Design and development experience in Big data, Java or Dat
At least 4+ years of working on data management domain with big data, Oracle, SQL or other database solutions. At least 2+ years of experience with Big Data & Analytics solutions Hadoop, MapReduce, Pig, Hive, Spark, Storm, Amazon Kinesis, AWS EMR, AWS RedShift, DynamoDB, Azure HDInsight, Azure Corta