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Design scalable patterns and architecture to support both batch and real-time data products & platform using big data technologies such as Hadoop, SQL Data Warehouse, EMR, Spark, DataBricks, Snowflake, Azure Synapse or other Cloud data warehousing technologies.
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Use Big Data technologies such as Kafka, Snowflake and related technologies to store, curate, process and publish datasets for consumption by downstream business users and applications. (2) Migrating data from various sources including Teradata, Oracle, SQL Server, and Salesforce using Azure Data Factory and Azure Databricks onto Snowflake.
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Technical Skills: Proficiency in SQL, database platforms (e.g., MySQL, Oracle, SQL Server), data warehousing, ETL processes, data modeling tools, and familiarity with cloud services (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data pipeline tools (Apache Kafka, NiFi.
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Extensive experience in data architecture, with a strong foundation in both relational databases and modern cloud data architectures, including big data technologies and data pipeline tools.
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Experience in any cloud data warehouse like Synapse, Big Query, Redshift, Snowflake. Optimize Databricks jobs for performance and scalability to handle big data workloads.
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Advanced experience in SQL in big data warehouse systems such as Snowflake, BigQuery, Databricks, etc. Internal knowledge of open source or related big data technologies. As a member of the Data Engineering Web3 team, you own the ETL/ELT pipelines and data warehouse that are used to analyze trends and activity in our Web3 product offerings.
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As the IT Data Architect at Schneider Electric's Sustainability Business, you will play a crucial role in shaping the organization's data strategy, ensuring it aligns seamlessly with its business objectives and digital transformation initiatives, to harness the power of data as a strategic asset.
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Familiarity with big data technologies such as Spark, Snowflake, Databricks, or EMR. You will be embedded on the Orchestration team that runs workflow scheduling applications and data ingestion infrastructure that helps power the analytics, operations, and data science behind our flagship streaming applications - Disney+, Hulu, ESPN+, and Star.
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O Experience with ecommerce/retail/supply chain data modeling is a big plus. o Strong experience with GCP o Experience with Big Query, Looker Studio o Experience with NoSQL databases (e.g., DynamoDB, Cassandra) and SQL databases (e.g., PostgreSQL, MySQL.
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Ability to design large scale distributed Big Data processing systems using technologies such as Hadoop, Spark, Kafka, etc. You will work with a diverse group of engineers, data scientists, and risk modelers to evolve a platform and application suite that mesh data and machine learning to tame an expanding array of use cases, including automated underwriting, pricing, directed claims handling, and cyber - the #1 threat to US national security, above nuclear weapons.
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Provide in-depth knowledge of GCP data services (Big Query, Cloud Storage, Dataflow, Looker/Tableau etc.) Extensive experience in data warehousing, data management, and business intelligence with proven expertise in Google Cloud Platform (GCP) and its data services (Big Query, Cloud Storage, Dataflow, etc.
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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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Big Data & Streaming: 2+ years using big data and/or streaming technologies (e.g. Apache Spark, Apache Kafka, Apache Flink) Data: Good understanding of data & data processing tools (e.g. Spark, Kafka, SQL), of relational database technologies and of analytics databases (e.g. Redshift, Vertica, Snowflake.
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At least 10 years of Experienced with all the tasks involved in administration of big data and Meta Data Hub such as Cloudera. The selected candidate will be responsible for orchestrating, deploying, maintaining and scaling cloud infrastructure targeting big data and platform data management (e.g., data warehouses, data lakes) including data access APIs. Prepares and manipulates data using Hadoop or equivalent.
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Experience with at least one major Massively Parallel Processing (MPP) or cloud database technology (Snowflake, Redshift, Big Query) Expanding, scaling, and standardizing the core foundational principles through consistent observability, lineage, data quality, logging, and alerting across all engineering teams in the Data organization is imperative to the creation of a single pane of glass.
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big data jobs Company: At T in Laramie, Wyoming
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