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The Data Warehouse Architect role involves strategically designing and implementing data warehouses, data marts, and data stores as well as requisite ETL (Extract, Transform, Load) and visualization (reporting) development while ensuring high levels of data availability.
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Hands-on experience in implementing Data Lake/Data Warehouse with technologies like – Databricks, Azure Synapse Analytics, SQL Database, AWS Lake formation. Design, Architect, Deploy, and maintain solutions on AWS and Databricks to provide secure and governed access to data for data scientist, data analysts and business users.
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Experience with Data Warehouse and ETL solutions such as SQL Server, Snowflake, Azure, Databricks, Informatica, or similar. Strong experience with data warehouse/data lake development techniques.
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The incumbent must have significant expertise in MS-SQL and proficiency in either Python or R. It is strongly preferred that the incumbent have experience with the Epic Systems Clarity data warehouse.
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Must have at least 5+ years of experience working as a Snowflake Data Architect and 10+ years of experience in Data Warehouse, ETL, and BI projects area. Snowflake Architect/Administrator who will be responsible for planning, designing, developing, and maintaining the snowflake data architecture, data models and standards for various Data Integration Data Warehouse projects in snowflake.
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This role will provide expertise to support the development of a Big Data / Data Lake system architecture that supports enterprise data operations for the District of Columbia government, including the Internet of Things (IoT) / Smart City projects, enterprise data warehouse, the open data portal, and data science applications.
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Strong Knowledge of Data Warehouses/Lakehouse architectures, Master Data Management, Data Quality Management, Data Integration, and Data Warehouse architecture.
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Job Title: Data Architect. Deep experience building data pipelines leveraging Spark (Azure Databricks or Apache Spark), Airflow. Experience Using airflow at scale, with integration to meta-data and lineage systems of record.
$165,000 - $180,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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The Data Architect will be held accountable for the following responsibilities: Define and implement the long-term technology strategy and innovations roadmaps across analytics, data engineering, and data platformsCreate standards, design patterns, and best practices for ETL development in an enterprise data warehouse environment.
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Minimum of 10 years of experience in big data, database and data warehouse architecture and delivery. AWS services, big data, data warehouse architecture, AWS Data Architect.
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Responsibilities: Performant has an immediate opening for a Sr. Data Warehouse Architect/EDI Specialist. The DWA/EDI specialist will architect, design, implement and maintain data interchange systems with external and internal partners and applications into the company’s modern data stack which include multi cloud platforms, Snowflake, and EDI pipelines.
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We are looking for a highly experienced and motivated Data ETL Architect to join our team This position will be responsible for designing and implementing data architectures to power our Databricks applications The successful candidate will have a deep understanding of data modelling data warehouse design and implementation and the ability to develop and maintain data pipelines.
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In-depth knowledge of SAP S/4HANA modules, including Finance Accounting and Managerial Accounting (Record To Report), Supply Chain (Procure to Pay) including inventory and Extended Warehouse Management, Sales and Distribution (Order to Cash), and Manufacturing (Plan to Produce) including Quality Management and Environment, Health and Safety.
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Cloud Lake and Warehouse Snowflake, S3 Data Lake, other comparable technologies. As a Data and Analytics Architect supporting Claim, you will collaborate with Technology and Business leaders and apply your knowledge of modern technology to influence and innovate solutions that impact the business.
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Understanding of enterprise data management concepts (Data Governance, Data Engineering, Data Science, Data Lake, Data Warehouse, Data Sharing, Data Applications.
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