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Propose new database architecture and support data migration from an existing Legacy system to a new structureCreate source-to-target mapping documents to transform the source data into the target warehouse and test final transformations.
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Work with a team with respect to discovery, design and delivery of data models, data governance models, data migration plans, data warehouse design and reporting components of applications using Microsoft tools.
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The Data Engineer will be responsible for standing up, maintaining, and scaling data operations such as external data transfers, data warehouse performance, our ETL tools such as Airflow, identifying data integrity issues, and developing documentation.
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Experience in Data Migration from RDBMS to Redshift/Snowflake cloud data warehouse. Provide direction on adoption of Cloud technologies (Redshift, Postgres, Snowflake,) and industry best practices in the field of data lakes and data warehouse architecture and modelling.
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Experience in building ETL / data warehouse transformation processes Direct experience of building data pipelines using Azure Data Factory and Apache Spark (preferably Databricks.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. As a member of the Data Engineering Blockchain team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity on the blockchain.
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At least 3 years of experience managing Cloud Data Warehouse database technologies, such as AWS Redshift, Snowflake, Databricks or similar. Design, configure, and manage Data Warehouse Database Systems on Cloud (AWS Redshift, EMR HBase and Snowflake.
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Responsibilities: Performant has an immediate opening for a Sr. Data Warehouse Architect/EDI Specialist. Technical expertise in enterprise-class data warehouse solutions and services, including advanced skills in areas such as:•Data warehousing methodologies and modelling techniques (Kimball, 3NF, Star Schema, Dimension modeling, Data Marts, Operational Data Stores, Data Vault 2.0 a plus)•Demonstrated skills with Matillion, WhereScape RED / 3D / Data Vault Express automation tools for SQL Server or Snowflake target destinations.
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Etc into pyspark Strong knowledge of cloud native data platform architectures, data engineering and data management Good knowledge of popular database and data warehouse technologies from Snowflake Microsoft Azure SQL Data Warehouse Demonstrated knowledge of data warehouse concepts.
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The Data Warehouse Developer will report directly to the Business Intelligence Manager, Enterprise Data Services (EDS) within the Division of Information Technology (DIT) at the University of Maryland, College Park. This is a C2 position which serves as an opportunity to contribute to a strategic initiative to improve data-driven decision-making on campus.
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What you’ll be responsible for:As a member of the Data Engineering - Business ETL team, you own the data warehouse and data pipelines that are used for financial and regulatory reporting.
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Performs analyses, development, and evaluation of data mining in the Snowflake cloud data warehouse environment which includes data design, database architecture, and data management utilizing Informatica PowerCenter, Intelligent Data Quality, and Enterprise Data Catalog.
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What you’ll be responsible for:As a member of the Data Engineering Blockchain team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity on the blockchain.
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Data Quality Systems & Strategy (~30%) Rebuild and streamline data warehouse SQL models that support CALPADS. This is alongside the team-wide ongoing data warehouse migration process to move our infrastructure and functionality to an updated and best in class solution with BigQuery and dbtCloud.
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Collaborate with the Finance or MP&L Application owners and the Ingestion team to “Land” and “Transform” the data in the Data warehouse on GCP BigQuery. Create data warehouse objects of raw data, and Analytical Model objects which are data products of customized data environments in GCP BigQuery (Data Warehouse), crafted to facilitate access of the information, with the goal of supporting scalable growth, sustainability, reusability, faster analytical solutioning and to accelerate delivery of business value.
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