Data Modeler Architect (Iselin, NJ)

Data Modeler Architect

Data Modeler Architect needs ETL development experience (i.e. Talend DataStage SSIS etc.).Data Modeler Architect requires Real time data streaming experience using Apache Kafka AWS Kinesis or the like. Experience with Snowflake or Zaloni. Certification such as AWS Certified Solutions Architect Big Data or Microsoft Azure Architect are preferable. Knowledge of Data Governance tools like Collibra. Responsive and proactive in answering questions. Excellent communication (written and oral) with senior leaders and peers facilitation interpersonal and collaborative skills. Strong desire to learn and research new frameworks and tools. Experience working with large scale Data Warehousing Data Lake and performance tuning. Establish data management methodology and standards for data modeling and data architecture. An undergraduate degree. A post-graduate degree in Data or Analytics is favorable. A minimum of 8 years of experience in application development with broad knowledge of Investment Management industry operations and market data providers 6 or more years of experience with data modeling. 4 or more years of experience in industry standard techniques for data modeling specifically in Dimensional modeling. 4 or more years of experience developing models for Business Intelligence solutions. 4 or more years of experience with Oracle MySQL or SQL Server. 4 or more years of experience with advanced SQL. 2 or more years of experience with Hadoop Hive Nifi Spark Dremio Presto or Impala. 2 or more years of experience working on cloud services like Amazon S3 Azure Storage or hybrid cloud services like Hadoop Ozone. Data Modeler Architect duties Architect design and implement the data pipeline and business intelligence solutions to the entire organization. Review the business process and conceptualize the entities that interoperate within the business process. Determine how the various entities are related and develop entity relationship diagrams that represent the connections among the entities. Collaborate with the BI and Analytics teams on creating the optimized reusable semantic model complete with metadata and lineage information. Collaborate with the enterprise data team to incorporate modern data governance metadata management data quality into our architectural approach. Define design and document data layers interfaces and flows with the understanding of use across the enterprise. Assist Agile Scrum teams with planning scoping and creation of technical solutions for new product capabilities through continuous integration and delivery. Liaise with a global team for resolving technical dependencies issues and risks. Build a metadata repository to structure the data for better management and efficient access. Establish data management methodology and standards for data modeling and data architecture.