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The Lead Data Engineer is 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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Cloud & Big Data Integration: Lead the migration and integration of data systems to cloud environments (AWS, Azure, GCP) and implement big data solutions as needed for advanced analytics and reporting.
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Experience in developing partner led sales in collaboration with data platform and tool vendorsIn-depth knowledge of big data technologies such as Hadoop, Spark, Kafka, and cloud platforms such as AWS, Azure, GCP, Snowflake, Databricks, etc.
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Would be preferred to have executed end to end implementation/migration of a Data Warehouse and Big Data (Hadoop) project from on prem to GCP (using Google BigQuery, DataFlow, DataProc etc.
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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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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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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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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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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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Big Data Technologies: Hadoop, Spark, Athena, materialized views. Data Visualization: Tableau, Looker, Power BI, Quicksight. Highly experienced Full stack Engineer with expertise in cloud engineering, data engineering, and data warehousing, particularly within the AWS and google cloud ecosystem.
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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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Responsibilities: 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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Hands-on experience with AWS big data analytics, Redshift, Kinesis, Lambda, Glue catalog, Athena, Airflow, Databricks, Python, Kafka, Spark and PySpark. Experience understanding of relational, structured/unstructured and semi-structured data with designing data lake, data governance, data lineage and data quality.
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Experience with Big Data technologies (Snowflake, Databricks/Spark, Trino). Has knowledge of data engineering best practices (data discovery, data documentation, infrastructure development/deployment, and information security.
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big data jobs Company: At T in Laramie, Wyoming
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